Smart contract enabled blockchain platform

Abstract

Systems and methods for implementing a C3N smart contract enabled blockchain platform. The platform employs a Proof-of-Reputation (PoR) consensus mechanism in which validator nodes are selected based on a C3N Score — a multi-dimensional trust score comprising a weighted composite of eight sub-scores drawn from performance, opinion, and reputation categories — stored on a distributed ledger not controllable by any single entity. The platform reduces the time and cost of building custom cryptocurrency blockchains: a business inputs its rules using the C3N Integrated Development Environment (IDE) or Command Line Interface (CLI), and the platform generates concrete smart contract implementations of pre-fabricated blockchain interfaces automatically. Network routing is conditioned on trust scores, such that only nodes meeting a minimum score threshold participate in routing and consensus.

Description

Attorney Docket No. 95814-0021SMART CONTRACT ENABLED BLOCK CHAIN PLATFORMCROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U. S. Provisional Patent Application No.63 / 760,459 filed on February 19, 2025, entitled “SMART CONTRACT ENABLED BLOCK CHAIN PLATFORM”, the contents of which are hereby incorporated herein by reference in its entirety for all purposes.

[0002] This application also incorporates by reference in their entireties for all purposes: U. S. Provisional Patent Application No. 63 / 345,785 filed on May 25, 2022 entitled “C3N-BASED SYSTEMS, NETWORKS, AND ECOSYSTEMS”; U. S. Provisional Patent Application No.63 / 858,031 filed on August 5, 2025 entitled “COLLISION-FREE ALPHANUMERIC IDENTIFIER GENERATION WITH PROBABILISTIC CHARACTER SET DISTRIBUTION, CONTEXT-AWARE VISUAL DISAMBIGUATION, HIERARCHICAL DELIMITER SYSTEM, AND ADJACENCY RESTRICTION RULES”; U. S. Provisional Patent Application No. 63 / 867,313 filed on August 20, 2025 entitled “SYSTEM AND METHOD FOR TRUE CONTINUOUS INFRASTRUCTURE DELIVERY WITH AUTONOMOUS SELF-HEALING, SELF-TESTING, AND SELF-DOCUMENTING CAPABILITIES”.TECHNICAL FIELD

[0003] Embodiments of the present disclosure relate to distributed ledger technology, and more particularly to: (1) contextual trust score evaluation using signed-polarity dimension weighting and hard-gate disqualification mechanisms; (2) self-sovereign, per-item score disclosure with firewall-semantics access control; (3) financial capacity and network quality dimensions for multi-dimensional trust scoring; (4) hierarchical network node connectors using Triple C3N Number addressing for privacy-preserving routing; (5) time-decay weighting of historical subscore records using versioned on-ledger decay configuration objects; (6) score stability measurement as a certified on-ledger sub-score governing consensus eligibility; (7) graph-theoretic rater independence scoring applied to opinion-category inputs to resist coordinated score manipulation; (8) categorical hard-gate disqualification of nodes upon severe misconduct events154252081.1Attorney Docket No. 95814-0021via an on-ledger Conduct Flag Registry; (9) on-ledger score dispute workflows with provisional computation holds and escalating arbitration; (10) certified regulatory compliance attestations issued through designated on-ledger authority infrastructure; and (11) event-driven real-time score propagation with cache invalidation tokens broadcast to trust-gated routing and consensus components.BACKGROUND

[0004] Creating a custom cryptocurrency blockchain presents significant barriers across various categories. Technical expertise is critical, as blockchain development requires advanced knowledge of cryptography, consensus mechanisms, scalability, and security. The financial burden is substantial, with high initial development costs, ongoing maintenance expenses, and potential fees for regulatory compliance and exchange listings. Businesses must also overcome market and adoption challenges, including building trust, achieving network effects, and competing with established blockchains. The legal and regulatory landscape adds further complexity, as jurisdictions worldwide continue to develop their cryptocurrency frameworks.

[0005] Creating a cryptocurrency token offers businesses significant benefits, particularly in customer engagement and operational efficiency. Tokens can be leveraged for loyalty and reward programs, providing a seamless, transparent way to incentivize customer behavior, boost engagement, and foster long-term loyalty. Unlike traditional points systems, tokens can have real-world value and be traded, adding an extra layer of appeal for customers. Additionally, tokens enable smart contract automation, allowing businesses to streamline operations by automating processes such as payments, service activations, and compliance verification.Limitations of Existing Approaches

[0006] Existing blockchain platforms present limitations that the present disclosure addresses. Public blockchain networks such as Ethereum rely on a virtual machine to execute smart contracts written in domain-specific languages. This architecture introduces execution overhead and constrains performance compared to native compiled code. Ethereum’ s consensus mechanism relies on computational expenditure or token holdings, which is energy-intensive and concentrates influence among large token holders rather than rewarding demonstrated network performance.254252081.1Attorney Docket No. 95814-0021

[0007] Permissioned enterprise blockchain platforms such as Hyperledger Fabric employ endorsement policies that designate specific pre-approved peer organizations. While this improves throughput relative to public blockchains, infrastructure is typically deployed and controlled by a single enterprise entity or a small consortium, concentrating control and failing to provide distributed-ownership guarantees.

[0008] The present disclosure addresses these limitations by providing a blockchain platform that: (1) employs a Proof-of-Reputation (PoR) consensus mechanism that selects validator nodes based on a multi-dimensional C3N trust score reflecting demonstrated network performance rather than computational expenditure or token holdings; (2) requires that the underlying infrastructure be collectively owned by at least two separate entities, preventing centralized control; and (3) integrates network routing conditioned on trust scores, such that only nodes meeting a minimum trust threshold may participate in routing and consensus.BRIEF DESCRIPTION OF THE DRAWINGS

[0009] FIG. 1 illustrates a block diagram of an example machine upon which any of one or more techniques (e g., methods) may be performed, in accordance with one or more example embodiments of the present disclosure.

[0010] FIG. 2 illustrates a system architecture diagram, in accordance with one or more example embodiments of the present disclosure.

[0011] FIG. 3 illustrates a simplified blockchain framework, in accordance with one or more example embodiments of the present disclosure.

[0012] FIG. 4 illustrates a smart contract comprising multiple contract types, in accordance with one or more example embodiments of the present disclosure.

[0013] FIG. 5 illustrates a C3N blockchain framework supporting multiple blockchains, in accordance with one or more example embodiments of the present disclosure.

[0014] FIG. 6 illustrates a network node connector for connecting nodes, in accordance with one or more example embodiments of the present disclosure.354252081.1Attorney Docket No. 95814-0021

[0015] FIG. 7 illustrates a SDN cloud, in accordance with one or more example embodiments of the present disclosure.

[0016] FIG. 8 illustrates a sequence diagram for the end-to-end request flow through the SDN fabric controller and trust scoring service, in accordance with one or more example embodiments of the present disclosure.

[0017] FIG. 9 illustrates a C3N IDE, in accordance with one or more example embodiments of the present disclosure.

[0018] FIG. 10 illustrates the Time-Decay Weight Vector (TDWV) architecture, showing per-dimension decay function selection, half-life parameterization, minimum weight floor enforcement, and composition with the Context Weight Vector in a two-stage scoring pipeline, in accordance with one or more example embodiments of the present disclosure.

[0019] FIG. 11 illustrates the Score Stability Index (SSI) computation pipeline, showing rolling variance computation over a configurable time window, normalization to the [0.0, 10.0] sub-score scale, on-ledger certification, and hard-gate integration within the CWV evaluation for validator election disqualification, in accordance with one or more example embodiments of the present disclosure.

[0020] FIG. 12 illustrates the Rater Independence Coefficient (RIC) computation, showing shortest-path graph distance computation within the C3N connection registry, clique density analysis, the signed on-ledger clique discount record, and per-entry RIC multiplier application within the weightedAverage computation for opinion-category sub-scores, in accordance with one or more example embodiments of the present disclosure.

[0021] FIG. 13 illustrates the Conduct Flag Registry (CFR), Score Dispute Protocol (SDP), and Score Event Bus (SEB) as integrated on-ledger components, showing the CFR hard-gate bypass of composite scoring, the SDP provisional hold state machine with arbitration tier escalation, and the SEB event-trigger and cache invalidation token propagation path to fabric controllers and consensus modules, in accordance with one or more example embodiments of the present disclosure.454252081.1Attorney Docket No. 95814-0021

[0022] Certain implementations will now be described more fully below with reference to the accompanying drawings, in which various implementations and / or aspects are shown. However, various aspects may be implemented in many different forms and should not be construed as limited to the implementations set forth herein; rather, these implementations are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art. Like numbers in the figures refer to like elements throughout. Hence, if a feature is used across several drawings, the number used to identify the feature in the drawing where the feature first appeared will be used in later drawings.DETAILED DESCRIPTION

[0023] Techniques described herein may be utilized to bridge the gap for business entities, making it cost effective to rapidly build their own cryptocurrency blockchain.

[0024] The present disclosure presents one or more illustrative, non-limiting embodiments for implementing blockchain platforms (e.g., based on a C3N architecture) for plugging in a business entity’s logic into concrete implementations of pre-fabricated blockchain software interfaces, where these smart contracts run their logic within the framework of the C3N blockchain network. C3N provides the infrastructure and plumbing as well as the core blockchain transaction processing engine.

[0025] Systems and methods for implementing a C3N smart contract enabled blockchain platform. A blockchain platform system with an energy-efficient consensus mechanism called Proof-of-Reputation (PoR), wherein validator nodes are selected based on reputation. This system reduces the time to market and major costs of building custom cryptocurrency blockchains. A business inputs their business rules and selects blockchain configurations using the C3N Integrated Development Environment (IDE) tooling or C3N smart contract platform Command Line Interface (CLI) application. The system will scale automatically to meet demand.

[0026] In at least one embodiment, a system for implementing a smart contract enabled blockchain platform is disclosed herein. The system may comprise: a blockchain infrastructure layer configured to provide network routing, resource management, service discovery, container orchestration, risk rating services, node management, chain management, and messaging services; a plurality of blockchain interfaces defining operations for blockchain types, the plurality of 554252081.1Attorney Docket No. 95814-0021blockchain interfaces being software constructs that indicate capabilities of the plurality of blockchain interfaces but not how the capabilities are implemented; an integrated development environment configured to receive rules or logic from an entity; and a smart contract engine configured to generate concrete smart contract implementations based on the received rules or logic, wherein the concrete smart contract implementations implement the capabilities indicated by the plurality of blockchain interfaces

[0027] In at least one embodiment, a system for implementing a smart contract enabled blockchain platform is disclosed herein. The system may comprise:a blockchain infrastructure layer configured to provide network routing, resource management, service discovery, container orchestration, risk rating services, node management, chain management, and messaging services;a plurality of blockchain interfaces defining operations for blockchain types, the plurality of blockchain interfaces being software constructs that indicate capabilities of the plurality of blockchain interfaces but not how the capabilities are implemented;an integrated development environment configured to receive rules or logic from an entity; anda smart contract engine configured to generate concrete smart contract implementations based on the received rules or logic, wherein the concrete smart contract implementations implement the capabilities indicated by the plurality of blockchain interfaces.

[0028] One or more systems described herein may be further characterized whereby the plurality of blockchain interfaces including at least one of: an identity management interface, a financial interface, an asset interface, a governance interface, a messaging interface, and a utility interface.

[0029] One or more systems described herein may be further characterized whereby the asset interface defines operations for at least one of: real world assets, royalties, identity tokens, and non-fungible tokens (NFTs).654252081.1Attorney Docket No. 95814-0021

[0030] One or more systems described herein may be further characterized whereby the governance interface defines operations for at least one of: voting, treasury management, and proposal execution.

[0031] One or more systems described herein may be further characterized whereby the blockchain infrastructure layer further comprises a software-defined networking component configured to establish tunnels between network nodes for smart contract execution.

[0032] One or more systems described herein may be further characterized whereby the software-defined networking component comprises a fabric controller configured to provide routing decisions to data plane devices using a pull-based routing approach, wherein the data plane devices request routes when needed rather than maintaining complete routing tables.

[0033] One or more systems described herein may be further characterized whereby the blockchain infrastructure layer implements a Proof-of-Reputation consensus mechanism, wherein validator nodes are selected based on reputation.

[0034] One or more systems described herein may be further characterized whereby the blockchain infrastructure layer is configured to support a plurality of distinct blockchains, each blockchain having respective smart contract implementations for the plurality of blockchain interfaces.

[0035] In at least one embodiment, a method for implementing a smart contract enabled blockchain platform is disclosed herein. The method may comprise:providing, by a blockchain infrastructure layer, network routing, resource management, service discovery, container orchestration, risk rating services, node management, chain management, and messaging services;defining, by a plurality of blockchain interfaces, operations for blockchain types, the plurality of blockchain interfaces being software constructs that indicate capabilities of the plurality of blockchain interfaces but not how the capabilities are implemented;754252081.1Attorney Docket No. 95814-0021receiving, by an integrated development environment, rules or logic from an entity; andgenerating, by a smart contract engine configured to generate concrete smart contract implementations based on the received rules or logic, wherein the concrete smart contract implementations implement the capabilities indicated by the plurality of blockchain interfaces.

[0036] One or more method described herein may be further characterized whereby the blockchain infrastructure layer further comprises a software-defined networking component configured to establish tunnels between network nodes for smart contract execution.

[0037] One or more method described herein may be further characterized whereby the software-defined networking component comprises a fabric controller configured to provide routing decisions to data plane devices using a pull-based routing approach, wherein the data plane devices request routes when needed rather than maintaining complete routing tables.

[0038] One or more method described herein may be further characterized whereby the blockchain infrastructure layer implements a Proof-of-Reputation consensus mechanism, wherein validator nodes are selected based on reputation.

[0039] One or more method described herein may be further characterized whereby the blockchain infrastructure layer is configured to support a plurality of distinct blockchains, each blockchain having respective smart contract implementations for the plurality of blockchain interfaces.

[0040] In at least one embodiment a non-transitory computer-readable medium stores executable instructions that, as a result of execution by one or more processors of a computer system, cause the computer system to perform one or more processes described in this disclosure. The non-transitory computer-readable medium may store instructions that cause a computer system to:provide a blockchain infrastructure layer for network routing, resource management, service discovery, container orchestration, risk rating services, node management, chain management, and messaging services;854252081.1Attorney Docket No. 95814-0021define, for a plurality of blockchain interfaces, operations for blockchain types, the plurality of blockchain interfaces being software constructs that indicate capabilities of the plurality of blockchain interfaces but not how the capabilities are implemented;receive, by an integrated development environment, rules or logic from an entity; andgenerate, by a smart contract engine configured to generate concrete smart contract implementations based on the received rules or logic, wherein the concrete smart contract implementations implement the capabilities indicated by the plurality of blockchain interfaces.

[0041] One or more non-transitory computer-readable media described herein may be further characterized whereby the blockchain infrastructure layer is implemented as a C3N blockchain infrastructure.

[0042] Various techniques described herein may relate to or otherwise utilize a C3N blockchain network. A C3N blockchain infrastructure is described in connection with U. S. Provisional Patent Application No. 63 / 345,785 filed on May 25, 2022, entitled “C3N-BASED SYSTEMS, NETWORKS, AND ECOSYSTEMS” to Sheehan, the contents of which are incorporated by reference in their entirety.Smart Contract Data Structure and Execution

[0043] In various embodiments, a smart contract managed by the smart contract engine is represented by a data structure comprising three components. First, a contract id, which is computed as the cryptographic hash of the contract’s contents. The smart contract is located by the hash of its contents and may thereby be stored on multiple distributed nodes. Second, a code field comprising the executable rules of the contract. Third, a parties field identifying the contracting parties by their C3N addresses. The smart contract may be stored in an encrypted form in a distributed file system, and a public key of each contracting party is stored alongside the smart contract, wherein either contracting party may decrypt the smart contract using Shamir’s Secret Sharing Algorithm without the unilateral cooperation of any single party.

[0044] In various embodiments, execution of a smart contract proceeds via the following protocol. A party that owns or is authorized to invoke a contract issues a run command of the form run(contractld, party A, partyB), passing its identity token. The smart contract worker node verifies 954252081.1Attorney Docket No. 95814-0021the identity token of the invoking party. Using the contractld, the worker node locates the contract in the distributed file system, decrypts the contract code, decompresses it, and executes it in a containerized environment.Proof-of-Reputation (PoR) Consensus and C3N Score

[0045] In various embodiments, the blockchain infrastructure layer implements a Proof-of-Reputation (PoR) consensus mechanism, wherein validator nodes are selected based on reputation.

[0046] As used herein, “reputation” in the context of the Proof-of-Reputation consensus mechanism refers to the multi-dimensional C3N Score comprising a weighted composite of the eight sub-scores described herein.

[0047] In various embodiments, the Proof-of-Reputation consensus mechanism employs a multi-dimensional C3N trust score (the “C3N Score”) to evaluate the reputation of each node in the network. The C3N Score is a weighted composite of eight sub-scores drawn from three categories:Performance category: (1) SLA transaction history — a record of the node’s fulfillment of service level agreement obligations across prior transactions; and (2) citizenship — a continuous, scored measure of a node’s adherence to network conduct standards and active participation in its assigned roles within the C3N ecosystem. The citizenship sub-score is reduced by confirmed offenses against ecosystem integrity (including denial-of-service attacks, unauthorized access to other nodes, and failure to fulfill governance or consensus obligations) and by a node operator’s failure to actively perform required governance tasks. For non-interactive entities, the citizenship sub-score is computed solely from compliance history and excludes governance participation metrics. A sustained degradation of the citizenship sub-score below the minimum threshold results in suspension of the node’s validator privileges and removal from cluster leader candidacy.Opinion category: (3) manager approval rating — ratings provided by node managers or cluster leaders who have directly observed the node’s performance; (4) overall star rating — aggregate star ratings received from all network participants; and (5) followed star rating — star ratings weighted by the network membership of the raters.1054252081.1Attorney Docket No. 95814-0021Reputation category: (6) vouched-for points — endorsements provided by other C3N network members; (7) industry certifications — verified professional credentials relevant to the services the node provides; and (8) test scores — results of standardized competency assessments administered by the C3N platform.

[0048] The formula for computing the C3N Score is made available to all C3N network participants. The following is illustrative source code that may be used to compute the C3N Score: package maintype Performance struct {slaTxHistory [ ] intcitizenship [ ] inttype Opinion struct (mgrApprovalRating [ ] intoverallStarRating [ ] intf ollowedStarRating [ ] inttype Reputation struct {vouchedForPoints [ ] intindustryCerts [ ] inttestScores [ ] intfunc weightedAverage ( intAry [ ] int, weight int) ( result int) {if len (intAry) == 0 { return 0 }sum 0; dontCount: = 0; hasOneOrMore: = false1154252081.1Attorney Docket No. 95814-0021for num: = range intAry {if num == 0 { dontCount++ } else { sum += num; hasOneOrMore = true }if! hasOneOrMore { return 0 }return (sum / (len (intAry) - dontCount) ) * weightfunc C3NScore (p Performance, o Opinion, r Reputation) int {perf: = weightedAverage (p. slaTxHistory, 1 ) + weightedAverage (p. citizenship, 1 )opin: = weightedAverage ( o. mgrApprovalRating, 1) +weightedAverage (o. overallStarRating, 1) +weightedAverage (o. f ollowedStarRating, 1 )rep: = weightedAverage ( r. vouchedForPoints, 1 ) +weightedAverage ( r. industryCerts, 1 ) +weightedAverage ( r. testScores, 1 )return (perf + opin + rep) / 8

[0049] The weights applied to each sub-score and to the composite calculation may be configured by the network operator; in one embodiment, equal weights are applied as shown in the illustrative source code above.Leader Election

[0050] In various embodiments, the C3N Score governs leader election within a cluster of nodes. As soon as the members of a node group are assembled, the nodes are ordered based on their C3N Score. The node with the highest C3N Score is designated the leader. In the event that1254252081.1Attorney Docket No. 95814-0021multiple nodes share the same C3N Score, the node with the earliest registration timestamp (created_at) is selected as the leader. In the rare case where multiple nodes share both the same C3N Score and the same registration timestamp, the node with the lowest MAC address is selected as the leader. All nodes in the cluster are provided with the trust scores of all other nodes to enable distributed tie-resolution without a central coordinator.Resource Manager and Fabric Controller

[0051] In at least one embodiment, a C3N resource manager provides a comprehensive configuration to a fabric controller. A host submits a registration to the fabric controller — for instance, establishing a relationship between host l and host_2. The fabric controller stores a route between host_l and host_2 in its local cache. Upon receiving a registration, the fabric controller requests the C3N Score for each registered host from a C3N rating service. The C3N rating service is powered by, and backed by, a distributed ledger (e.g., the C3N blockchain network) that cannot be manipulated or centrally controlled by any single entity.

[0052] When a user attempts to access a resource — for instance, a webpage or application accessible via a C3N Super App — the following routing protocol executes. A local DNS cache determines the address of the target resource. If it is determined that the requested content is accessible via host l, and the user is operating from host_2, a route from host_2 to host l is required. Host_2 submits a connection request to a local switch (sw-2). Switch sw-2 routes a request for a path to host_l to the fabric controller. The fabric controller evaluates the cached C3N Scores for both host l and host_2. If both scores satisfy the minimum threshold, the fabric controller returns the route to sw-2, which establishes a Layer 3 tunnel to the switch associated with host l. The fabric controller returns a route only if the trust scores of both the source and destination hosts satisfy a predetermined threshold; if either score fails to meet the threshold, the route request is denied.

[0053] The threshold score required for trust-gated operations, including validator selection and network routing, may be configured by the network operator; in one embodiment, the threshold is set at a minimum C3N Score of 6.0 on a scale of 0.0 to 10.0.

[0054] According to at least one embodiment, a blockchain framework system comprised of blockchain infrastructure, blockchain interfaces and a blockchain platform IDE (and tooling),1354252081.1Attorney Docket No. 95814-0021wherein business entities enter their business rules to code concrete smart contract implementations of the blockchain interfaces.

[0055] According to at least one embodiment one or more methods described herein are implemented such that the method further comprises enabling business rules coder to use the C3N blockchain platform IDE (and / or CLI) to enter business rules in C3N smart contracts.

[0056] According to at least one embodiment one or more methods described herein are implemented such that the method further comprises enabling a business blockchain administrator to further configure, deploy and monitor the workings, metrics, logs and analytics of their deployed blockchain via an admin page in the C3N super app.

[0057] According to at least one embodiment, an ecosystem is comprised of producers and consumers of C3N technologies, wherein business entities and / or individuals provide and consume resources sharing in the profits and benefitting from the products and services provided.

[0058] According to at least one embodiment one or more methods described herein are implemented such that the method further comprises enabling C3N producers to submit, using the C3N super app, their compute devices to provide compute resources for profit

[0059] According to at least one embodiment one or more methods described herein are implemented such that the method further comprises enabling C3N consumers to benefit from C3N producers, using the C3N super app.

[0060] In various embodiments, blockchain interfaces for identity (ID) Management capabilities provide for identity management, role-based access control (RBAC), supply chain applications, legal applications, etc.

[0061] In various embodiments, blockchain interfaces for financial capabilities provide for: DeFi exchange, lending, yield farm, insurance, etc.

[0062] In various embodiments, blockchain interfaces for asset-related capabilities provide for: Real World Assets, royalties, ID tokens, digital art (non-fungible tokens NFTs), etc.1454252081.1Attorney Docket No. 95814-0021

[0063] In various embodiments, blockchain interfaces for governance capabilities provide for: voting, treasury management, proposal execution, etc.

[0064] In various embodiments, blockchain interfaces for messaging-related capabilities provide for: topics, publish / subscribe channels, transformations, integrations, etc.

[0065] In various embodiments, blockchain interfaces for utility-related capabilities provide for: oracles, crosschain bridges, data storage, etc.

[0066] In various embodiments, techniques described herein provide for the implementation of infrastructure services. These infrastructure services may include infrastructure services for networking, including but not limited to: routing, resource management, service discovery and container orchestration, etc.

[0067] In various embodiments, techniques described herein provide for the implementation of infrastructure services. These infrastructure services may include infrastructure services for risk capabilities, including but not limited to: C3N rating (similar to a credit rating), monitoring, analytics, enforcement, etc.

[0068] In various embodiments, techniques described herein provide for the implementation of infrastructure services. These infrastructure services may include infrastructure services for Blockchain capabilities, including but not limited to: node management, chain management, blockchain management, etc.

[0069] In various embodiments, techniques described herein provide for the implementation of infrastructure services. These infrastructure services may include infrastructure services for Super Apps, including but not limited to: user interfaces (UI) for cryptocurrency wallet, merchant UI, admin UI, etc.

[0070] In various embodiments, techniques described herein provide for the implementation of infrastructure services. These infrastructure services may include infrastructure services for Messaging, including but not limited to: message router, message broker, message queue, etc.1554252081.1Attorney Docket No. 95814-0021

[0071] In various embodiments, techniques described herein provide for the implementation of infrastructure services. These infrastructure services may include infrastructure services for Integration, including but not limited to: API gateway, exchanges, banking, payment gateway, etc.

[0072] In various embodiments, techniques described herein provide for the implementation of Blockchain Interfaces. Blockchain interfaces may refer to software constructs that define what blockchain types must do, not how to do it.

[0073] In various embodiments, techniques described herein provide for the implementation of Blockchain Smart Contracts. Concrete implementation with the actual logic for the methods defined in each interface. Each blockchain brings its own protocol rules / smart contract implementations. For example, different blockchains may support different: lending models, legal requirements, user groups and access control rules, etc.

[0074] In various embodiments, techniques described herein relate to implementing infrastructure that all blockchain networks require - such as networking, risk services, blockchain services, messaging, etc.Multi-Tier Transaction Validation Use Case

[0075] In various embodiments, the blockchain platform described herein supports an end-to-end transaction validation workflow. A transaction subject to configurable business rules — such as per-transaction limits, aggregate period limits, geographic restrictions, and regulatory compliance thresholds — must be validated before it is committed to the blockchain. Such a workflow may be implemented across four tiers: (1) a decentralized application (dApp) performing initial validation using locally cached rule parameters; (2) a backend Transaction Limit Service performing authoritative validation; (3) an oracle service synchronizing validated transaction data to the blockchain network; and (4) an on-chain smart contract performing final verification. This layered architecture ensures that transaction validation is performed redundantly at multiple trust boundaries, with the blockchain serving as the final arbiter of transaction validity.

[0076] The C3N Smart Contract Markup Language (C3SML) enables a developer to express business rules once in a single, language-agnostic specification, and the C3N platform1654252081.1Attorney Docket No. 95814-0021toolchain generates the corresponding implementations for each application tier automatically, eliminating cross-tier logic drift.Financial Capacity Sub-Score (FCS) and Network Quality Sub-Score (NQS)

[0077] In various embodiments, the C3N Score further incorporates two additional subscores that extend the trust evaluation framework beyond behavioral and credentialing history.

[0078] Financial Capacity Sub-Score (FCS): A scored representation of an entity’s financial standing within the C3N ecosystem, computed entirely from native C3N platform data including wallet balances, digital asset holdings, and transaction history maintained by the C3N Super App. No external data source, third-party integration, or self-reported input is used. The FCS is stored on the distributed ledger as a certified tier integer (Tier 1 through Tier 6), representing a defined financial capacity band rather than a raw figure. The tier computation is performed within the platform’s HSM-backed infrastructure to prevent tampering with the computation process. The FCS tier, once certified, is an on-ledger object subject to the same immutability and audit guarantees as other ledger data. The FCS is recomputed on a schedule determined by the network operator whenever the underlying financial data changes materially.

[0079] Network Quality Sub-Score (NQS): A graph-propagated measure of the financial quality of an entity’s professional network within the C3N ecosystem. The NQS draws from a dedicated connection registry distinct from the vouched-for endorsement graph, though vouched-for connections are a subset of the connection registry. Only C3N-registered, KYC / AML-verified entities participate in the connection registry; unregistered entities cannot contribute to or appear in any NQS computation. Each registered connection’s contribution to the NQS is weighted by that connection’s own FCS tier and by their organizational relationship to the scored entity. The NQS is stored on the distributed ledger as a certified tier integer (Tier 1 through Tier 6) analogous to the FCS representation.

[0080] The NQS and FCS are independently computable sub-scores that may be incorporated into the C3N Score composite alongside the eight base sub-scores, subject to the weighting configuration of the applicable Context Weight Vector (e.g., as described in further detail below).1754252081.1Attorney Docket No. 95814-0021Context Weight Vector (CWV)

[0081] In various embodiments, the C3N Score is evaluated through a Context Weight Vector (CWV), a named and versioned configuration object stored on the distributed ledger that parameterizes how each sub-score dimension contributes to a contextual score for a specific role or evaluation purpose. The CWV enables the same underlying sub-score data to produce different contextual scores depending on the context in which an entity is being evaluated, because the same raw value may be a positive signal, an irrelevant datum, or a disqualifying indicator depending on the role being filled.

[0082] Each CWV specifies, for every sub-score dimension including FCS and NQS, a signed polarity value and a weight. The polarity value governs the direction of the dimension’s contribution: a polarity of +1 causes a higher raw value to raise the contextual score (normal positive contribution); a polarity of 0 suppresses the dimension entirely so that it neither helps nor penalizes the entity; and a polarity of -1 inverts the contribution so that a lower raw value raises the contextual score and a higher raw value lowers it. The weight parameter governs the magnitude of the contribution.

[0083] In various embodiments, a CWV further specifies a hard gate parameter for the FCS and NQS dimensions. A hard gate is a threshold that, when triggered, collapses the contextual score to a floor value of 0.0 regardless of all other dimensions. For a dimension with positive polarity, the hard gate triggers when the raw value falls below the specified threshold; for a dimension with negative polarity, it triggers when the raw value exceeds the specified threshold. The hard gate is not a weight reduction — it is a binary disqualification mechanism. For example, in an investor evaluation context, a hard gate on FCS ensures that an entity below a minimum financial capacity threshold is disqualified regardless of its SLA history, citizenship score, or vouched-for endorsements.

[0084] The following illustrative pseudocode describes contextual C3N Score computation:func contextualC3NScore (entity Entity, cwv ContextWeightVector) float64 { / / Step 1: Re-weight the base 8 sub-scores per context1854252081.1Attorney Docket No. 95814-0021base: = weightedAverageWithContextWeights (entity. c.3nScore,cwv. b a s e W e i g h t s ) / / Step 2: Hard gate evaluation — short-circuits all further computation if cwv. fcsHardGate {if cwv. fcsPolarity == 1 && entity, fcs < cwv. fcsGateThreshold { return SCORE FLOORif cwv. fcsPolarity == -1 && entity. fcs > cwv. fcsGateThreshold { return S C 0 R E _ F L 00 R / / Step 3: Apply FCS and NQS with signed polarityfcsContrib: = float 64 ( cwv. fcsPolarity) * float64 (entity. fcs) *cwv. fcs WeightnqsContrib: = f loat.64 ( cwv. nqsPolarity) * float64 (entity. nqs) *cwv. nqs Weightreturn (base + fcsContrib + nqsContrib) / ( 1 + cwv. fcsWeight +cwv. n q s W e i g h t;

[0085] A CWV is stored on the distributed ledger as a named, versioned object that may be authored by any C3N -registered entity with appropriate platform permissions, including blockchain operators, dApp developers, and marketplace administrators. The CWV schema comprises: a cwv_id string and version integer; a created_by C3N address; a baseWeights array of eight float64 values corresponding to the eight base sub-scores; fcsPolarity and nqsPolarity integers; fcsWeight and nqsWeight float64 values; fcsHardGate and nqsHardGate booleans; and fcsGate Threshold and nqsGateThreshold integers.1954252081.1Attorney Docket No. 95814-0021

[0086] Because the CWV is stored on-ledger, every contextual score computation is auditable: the CWV version used, the entity’s sub-score values at the time of computation, and the resulting contextual score are all recorded in an immutable computation log. This ensures that the basis for any trust-gated decision — including validator selection, network routing, and smart contract execution — can be inspected and verified by any authorized party.Score Disclosure Rule Engine

[0087] In various embodiments, the C3N platform implements a self-sovereign score disclosure system that gives each registered entity independent, granular control over which components of their C3N Score are visible to which querying parties. The default state for all score data is private: no score component is disclosed to any external party unless the entity has explicitly authorized disclosure through the rule engine described herein.

[0088] Score disclosure is controlled through per-item rule sets. Each disclosable item maintains an independent rule set. Disclosable items include: NQS TIER (the network quality score tier integer); NQS GRAPH (the underlying connection list with per-connection FCS tiers); VOUCHED FOR SCORE (the vouched-for sub-score as it contributes to the C3N Score composite); VOUCHED FOR GRAPH (the underlying endorsement graph identifying individual endorsers); C3N COMPOSITE (the full composite C3N Score); and SUB SC ORE: [name] for any individually named sub-score including FCS, citizenship, SLA transaction history, and others.

[0089] Each rule set evaluates disclosure requests using a firewall-semantics model with five specificity levels evaluated in order from most-specific to least-specific:Level 1 (QUICK): Irrevocable rules that short-circuit all other evaluation. A QUICK rule, once written, cannot be modified or deleted. Two classes of actor may write QUICK rules: (a) the entity themselves, as an exercise of self-sovereignty to create a permanent grant or permanent block; and (b) infrastructure-level regulatory authorities, which are platform-defined, explicitly enumerated entities whose designation is itself an on-ledger record specifying the authority’s C3N address, the identity of the entity that elevated them, the timestamp of elevation, and the legal or regulatory basis for the designation. Any entity may inspect all QUICK rules written against their own disclosure rule sets.2054252081.1Attorney Docket No. 95814-0021Level 2 (INDIVIDUAL): Rules matching the specific C3N address of the querying entity. An INDIVIDUAL rule overrides any GROUP, CONTRACT, BLOCKCHAIN, or DEFAULT rule for that specific querier.Level 3 (GROUP): Rules matching a C3N-registered group of which the querying entity is a verified member. A GROUP rule overrides any CONTRACT, BLOCKCHAIN, or DEFAULT rule for members of that group.Level 4 (CONTRACT): Rules matching the C3N address of the smart contract executing the query. A CONTRACT rule overrides any BLOCKCHAIN or DEFAULT rule for that specific contract.Level 5 (BLOCKCHAIN): Rules matching the C3N address of the blockchain on which the querying contract executes. A BLOCKCHAIN rule overrides the DEFAULT rule for all contracts on that blockchain.Level 6 (DEFAULT): BLOCK ALL. Applied when no higher-level rule matches.

[0028] The following pseudocode illustrates the evaluation sequence:FUNCTION evaluateDisclosure ( ruleSet, queryingEntity, contract, blockchain): FOR rule IN ruleSet WHERE rule. quick == true:IF rule matches queryingEntity OR rule applies globally:RETURN rule.action / / DISCLOSED or NOT_DISCLOSEDIF any INDIVIDUAL rule matches queryingEntity. c3nAddress:RETURN that rule.actionIF any GROUP rule matches any group queryingEntity is member of:RETURN that rule.actionIF any CONTRACT rule matches contract.c3nAddress:RETURN that rule. actionIF any BLOCKCHAIN rule matches blockchain. c3nAddress:2154252081.1Attorney Docket No. 95814-0021RETURN that rule. actionRETURN BLOCK / / DEFAULT

[0090] When a blockchain operator publishes terms requiring specific score disclosures, and a user accepts those terms, the platform writes BLOCKCHAIN-level PASS rules to the specified rule sets on the user’s behalf. These rules are revocable: the user may subsequently add CONTRACT-level or INDIVIDUAL-level BLOCK rules to claw back disclosure at finer granularity.

[0091] Each rule set is stored on the distributed ledger as a versioned, append-auditable object associated with the entity’s C3N address and the specific disclosable item. Each rule record comprises: level (DEFAULT, BLOCKCHAIN, CONTRACT, GROUP, INDIVIDUAL, or QUICK); target C3N address; from C3N address; action (PASS or BLOCK); quick boolean; authority C3N address; timestamp; and version integer.

[0092] When a disclosure query returns NOT DISCLOSED and the requesting smart contract required that score component as a condition of execution, contract execution halts. When the score component was optional, the contract proceeds with the score recorded as null.NQS Graph Disclosure and B-3 Propagation

[0093] In various embodiments, when an NQS GRAPH disclosure is authorized for a given querier, the platform traverses the entity’s connection registry and evaluates each connection’s own disclosure rule set against the same querying party. Each connection entry in the output is rendered at one of three resolution levels:Full entry: The connection’s rule set returns DISCLOSED for NQS GRAPH. The output shows the connection’s C3N address and FCS Tier.Anonymized entry: The connection has granted NQS TIER disclosure but not NQS GRAPH disclosure. The output shows [anonymized] and the FCS Tier, preserving financial weight without revealing identity.Redacted entry: The connection has granted neither NQS TIER nor NQS GRAPH disclosure. The output shows [redacted]. The connection’s existence is preserved in the count so the NQS computation reflects the actual graph size, but no information about the connection is revealed.2254252081.1Attorney Docket No. 95814-0021

[0094] No connection entries are omitted from the output. Omitting entries would distort the NQS computation by reducing the denominator of the weighted average. The graph count is always accurate; resolution of individual entries is governed by each connection’s own disclosure settings.Network Node Connector (NNC)

[0095] A “Network Node Connector” (NNC) is a network component in the C3N Blockchain Platform that intelligently routes requests between nodes by combining DNS resolution, Software-Defined Networking (SDN) switching, and tunnel-based routing to connect blockchain hosts securely. Each NNC is addressed and identified using the Triple C3N Number hierarchy (region_c3n:cluster_c3n:entity_c3n), and operates as the authoritative routing boundary for a given C3N cluster.

[0096] The C3N Blockchain Platform uses a hierarchical three-component addressing scheme derived from the collision-free C3N Number generator, wherein each component is a 10-character alphanumeric string encoded as an int64. The first component, region_c3n, identifies the geographic or administrative region and is used for macro-level inter-region packet forwarding. The second component, cluster_c3n, identifies the cluster boundary — the NNC that owns and manages internal node addressing for that cluster. The third component, entity _c3n, identifies the specific blockchain node, host, service account, or application within the cluster’s private address space.

[0097] Routing proceeds in two phases. In Phase 1 (public routing), the region_c3n and cluster c3n components of the destination Triple C3N address are resolved by the C3N routing fabric to identify and forward an incoming packet to the correct NNC. In Phase 2 (private resolution), the NNC resolves the entity _c3n component against its local binding table to identify and forward to the actual destination node within the cluster’s private address space. Internal node addresses are never exposed to the public routing fabric.

[0098] The owner of a C3N cluster may configure the NNC to manage the full namespace of entity _c3n identifiers within that cluster. This configuration capability allows the cluster owner to: register and bind entity _c3n identifiers to specific internal network node addresses (private IPs or overlay addresses) within the cluster; define access policies controlling which external2354252081.1Attorney Docket No. 95814-0021region: cluster addresses may initiate connections to specific internal entities; assign port ranges or reserved port mappings for different service types; and control the external visibility of entity _c3n records within the C3N routing fabric.

[0099] When a network packet arrives at an NNC addressed to region_c3n:cluster_c3n:entity_c3n, the NNC performs address translation analogous to a Network Address Translation (NAT) router: (1) Inbound Packet Receipt — the NNC receives the packet as the authoritative gateway for the cluster; (2) Source Address Rewriting — the NNC rewrites the source address, replacing the originating entity’s private or internal address with the NNC’s own public cluster_c3n identifier; (3) Port Assignment — the NNC assigns a unique outbound port to the session; (4) Translation Table Entry — the NNC logs the mapping of the assigned port to the originating internal entity _c3n in its session translation table; and (5) Forward — the packet is forwarded to its destination.

[0100] Because each NNC may itself reside within a larger cluster that has its own NNC, the C3N addressing architecture supports recursive, hierarchical address translation — a “Russian Doll” stack of cluster-within-cluster translations. In this model, an entity _c3n that is addressable within an inner cluster has its address rewritten at each NNC boundary as packets traverse outward through successively larger clusters.

[0101] All node identities within the NNC translation architecture are encoded as int64 values derived via c3n_to_int64() from their C3N string representations. No layer stores or transmits raw IP addresses as node identifiers. Every NNC translation table maps int64 values to int64 values plus assigned port numbers, forming a privacy-preserving, space-efficient routing chain in which the internal topology of any cluster remains opaque to all external observers. Temporal Decay and Recency Weighting

[0102] In various embodiments, each entry in a time-stamped sub-score history array — including the SLA transaction history and citizenship sub-score arrays — carries a recorded timestamp representing the time at which that entry was produced. The C3N platform introduces a Time-Decay Weight Vector (TDWV): a named, versioned configuration object stored on the distributed ledger that parameterizes how historical sub-score entries are weighted as a function of their age relative to the time of score computation.2454252081.1Attorney Docket No. 95814-0021

[0103] Each TDWV specifies, for each sub-score dimension to which it applies: (a) a decay function type, which may be EXPONENTIAL, LINEAR, or STEP; (b) a half-life parameter expressed in seconds, defining the rate at which older entries are down-weighted; and (c) a minimum weight floor, a value in [0.0, 1.0] below which no entry’s weight is reduced, ensuring that sufficiently old records retain non-zero evidentiary weight and preserving historical accountability. A TDWV may be defined independently per sub-score dimension, allowing, for example, SLA transaction history to decay more rapidly than citizenship conduct records, reflecting the differing relevance horizons of those dimensions.

[0104] The TDWV schema stored on the distributed ledger comprises: a tdwv id string and version integer; a created_by C3N address; a dimension identifier specifying the sub-score dimension governed; a decay function enumeration value (EXPONENTIAL, LINEAR, or STEP); a half life seconds integer; and a min weight floor float value. Because the TDWV is a ledger object, every decayed sub-score computation is independently reproducible: any party with the entity’s sub-score timestamps and the named TDWV version can verify the weighted computation result without access to any off-chain data.

[0105] The TDWV operates as a pre-processing stage executed before the Context Weight Vector (CWV) evaluation. For each historical entry in the applicable sub-score array, the system computes a decay weight w(t) as a function of elapsed time At since that entry was recorded, using the decay function and parameters specified by the applicable TDWV. The minimum weight floor is enforced: if the computed w(t) falls below min_weight_floor, it is raised to min_weight_floor. The resulting decay-weighted values are passed to the existing weighted Average computation, after which the CWV applies polarity and context weights in the normal manner. Deployments for which no TDWV is configured default to uniform weight across all historical entries, preserving backward compatibility with the base C3N Score computation.

[0106] When a TDWV version is updated on the distributed ledger, the trust score computation module generates a score recomputation event for all nodes whose sub-score arrays contain entries governed by that TDWV dimension. The recomputed scores are propagated to the consensus module and network routing controller, and the prior cached scores are invalidated. This ensures that a change to the decay configuration cannot persist silently in cached trust-gated2554252081.1Attorney Docket No. 95814-0021decisions, maintaining consistency between the on-ledger TDWV configuration and the live PoR validator selection state.

[0107] The TDWV architecture described herein is illustrated in FIG. 10.Score Stability Index

[0108] In various embodiments, the C3N platform computes and stores a Score Stability Index (SSI) for each node as a certified on-ledger sub-score. The SSI captures the consistency of a node’s performance over time, independently of the average level of that performance. Two nodes with identical composite C3N Scores may carry substantially different risk profiles if one has achieved that score consistently while the other has exhibited volatile performance across the measurement window. The SSI makes this distinction explicit and actionable within the PoR consensus mechanism.

[0109] The SSI is computed from the population standard deviation of a node’s performance sub-score values recorded within a configurable rolling time window. The rolling window boundaries — expressed as a trailing duration in seconds or a trailing transaction count — are stored in a named, versioned ledger object associated with the SSI computation configuration for the applicable deployment. The SSI is defined as: SSI = 1 - normalize(o_rolling / c m ax), where c rolling is the population standard deviation of the sub-scores within the rolling window and o_max is the theoretical maximum standard deviation on the [0.0, 10.0] scoring scale. The result is clamped to [0.0, 10.0] to align with the scale of all other C3N sub-scores.

[0110] The SSI is stored on the distributed ledger as a certified sub-score, subject to the same HSM-backed computation integrity guarantees as the Financial Capacity Sub-Score. The SSI ledger record comprises: the entity’s C3N address; the computed SSI value; the rolling window configuration object identifier and version; the timestamp and score range of the window used in the computation; and a certification hash. The SSI participates as a first-class C3N sub-score dimension: it is an independently disclosable item under the Score Disclosure Rule Engine and may be referenced as a named dimension in a Context Weight Vector (CWV).

[0111] In one embodiment, a CWV configured for a high-reliability validator role specifies a hard gate parameter on the SSI dimension with positive polarity: any node whose SSI falls below the configured threshold receives a contextual score of 0.0 and is excluded from the validator2654252081.1Attorney Docket No. 95814-0021election candidate set regardless of its composite C3N Score. This hard gate is structurally identical to the FCS and NQS hard gate mechanisms defined in Section

[0023] -

[0028] , and is enforced by the same contextual score computation module. The effect is that a node with an acceptable average performance level but unacceptably volatile behavior is categorically disqualified from high-reliability validator roles without modification to the base scoring architecture.

[0112] The Score Stability Index architecture described herein is illustrated in FIG. 11.Rater Independence Coefficient

[0113] In various embodiments, the C3N platform applies a Rater Independence Coefficient (RIC) to each input to an opinion-category sub-score — including vouched-for points and all star rating inputs — before those inputs are combined in the weightedAverage computation. The RIC is a per-input multiplier in [0.0, 1.0] that discounts the contribution of a rating source based on its proximity to and structural relationship with the subject node in the C3N connection registry. The RIC mechanism addresses the risk that a ring of KYC / AML-verified but coordinating entities could mutually inflate each other’s sub-scores by generating correlated, dependent opinion inputs that superficially resemble independent peer assessments.

[0114] The RIC for a given rater with respect to a given subject node is computed from two graph-theoretic signals derived from the C3N connection registry. First, a graph proximity penalty is computed as the normalized inverse of the shortest-path distance between the rater and the subject node in the connection registry graph; raters who are direct connections of the subject node receive the maximum proximity penalty, while raters at greater graph distance receive progressively smaller penalties, down to a proximity penalty of zero for raters with no graph path to the subject node within a configurable depth limit. Second, a clique density penalty is applied to any rater who is a member of a subgraph whose local clustering coefficient exceeds a configurable threshold. The combined RIC for a given rater-subject pair is: RIC = (1 - proximity_penalty) × (1 - clique_discount), where clique_discount is the discount factor assigned to the rater’s identified high-density cluster.

[0115] Clique identification runs as a periodic computation at each scoring epoch. Its output — the set of identified high-density subgraphs and their assigned discount factors — is published as a signed, versioned record on the distributed ledger. The clique record is publicly2754252081.1Attorney Docket No. 95814-0021auditable: any participant may inspect the identified clusters, the clustering coefficient values that triggered identification, and the discount factors applied. This transparency distinguishes the RIC mechanism from an opaque filter: nodes can observe when their cluster has been identified as high-density and take steps to diversify their connection graph.

[0116] In addition to clique detection, the platform maintains a Mutual Endorsement Registry as a ledger object tracking endorsement pairs where both parties have endorsed each other. For each mutual endorsement pair, both parties ’RIC values for the mutual endorsement transaction are reduced by a configurable mutual endorsement discount factor stored on-ledger. Mutual endorsements are not disqualified but are transparently down-weighted; the Mutual Endorsement Registry is auditable, allowing a node to demonstrate that its endorsement relationships are unilateral and therefore carry full RIC weight.

[0117] The RIC is applied as a pre-weight multiplier to each opinion-category input immediately before the weightedAverage computation. The RIC -adjusted input value is: adjusted_input = raw_input x RIC(rater, subject). No change to the weightedAverage function signature or the CWV architecture is required. The threshold parameters governing clique identification and the mutual endorsement discount factor are stored as named, versioned ledger configuration objects, making the RIC computation independently verifiable and configurable by the network operator without modifying the platform software.

[0118] The Rater Independence Coefficient architecture described herein is illustrated in FIG. 12.Conduct Flag Registry

[0119] In various embodiments, the C3N platform maintains a Conduct Flag Registry (CFR): an on-ledger registry of severity-classified misconduct events associated with specific node C3N addresses. The CFR provides a categorical disqualification mechanism that operates independently of and prior to the composite C3N Score computation, ensuring that severe misconduct events cannot be diluted by averaging with a node’s other sub-scores.

[0120] Each CFR entry is classified at one of three severity levels: MINOR, MAJOR, or DISQUALIFYING. A MINOR entry is recorded as a ledger event that contributes to the citizenship sub-score reduction in the normal manner. A MAJOR entry reduces the citizenship2854252081.1Attorney Docket No. 95814-0021sub-score by a configurable, ledger-stored severity weight and is a separately disclosable item under the Score Disclosure Rule Engine. A DISQUALIFYING entry triggers an immediate hard gate: the node’s composite C3N Score and all contextual scores derived from it are collapsed to the floor value of 0.0, removing the node from the validator election candidate set and blocking network routing access, without any requirement that the effect propagate through the composite scoring computation. The DISQUALIFYING hard gate effect persists until the CFR entry is resolved through the Score Dispute Protocol (as described in further detail below) or administratively cleared by an authorized party.

[0121] DISQUALIFYING CFR entries are issuable only by explicitly authorized parties. The set of entities authorized to issue DISQUALIFYING entries is defined using the same on-ledger regulatory authority designation infrastructure that governs QUICK rule issuance in the Score Disclosure Rule Engine. Specifically, an entity may issue DISQUALIFYING CFR entries only if its C3N address appears in the on-ledger regulatory authority registry with a designation record specifying the authority to issue CFR entries of that severity level, the C3N address of the entity that granted that authority, the timestamp of designation, and the legal or regulatory basis. This reuse of the existing trust root architecture ensures that no new privileged actor class is introduced and that the authorization chain for any DISQUALIFYING entry is fully traceable through the distributed ledger.

[0122] Each CFR entry record stored on the distributed ledger comprises: the subject node’s C3N address; the issuing authority’s C3N address; the severity level (MINOR, MAJOR, or DISQUALIFYING); a structured event type classification (including categories such as fraud, unauthorized access, denial-of-service, contract breach, and governance violation); a free-text description field; a reference hash linking to any supporting on-ledger transaction records; the timestamp of issuance; and the current resolution status (ACTIVE, DISPUTED, or RESOLVED). The CFR is a separately disclosable item under the Score Disclosure Rule Engine: a node may control which parties can query its CFR history, subject to QUICK rules issuable by designated regulatory authorities that may require mandatory disclosure in specific contexts. The CFR architecture described herein is illustrated in FIG. 13.2954252081.1Attorney Docket No. 95814-0021Score Dispute Protocol

[0123] In various embodiments, the C3N platform implements a Score Dispute Protocol (SDP): a formal on-ledger workflow through which a node may contest a specific score input that it believes was incorrectly attributed, maliciously submitted, or fraudulently certified. The SDP defines the ledger state machine, data structures, and resolution procedures governing the dispute lifecycle.

[0124] A node initiates a dispute by submitting a dispute transaction to the distributed ledger referencing the specific score input being contested by its on-chain content hash. The referenced input may be an SLA failure record, a star rating entry, a CFR entry, or a certification record. Upon receipt of a valid dispute transaction, the platform transitions the referenced input to a DISPUTED state in the ledger and applies a provisional hold: the disputed entry is suspended from contribution to the node’s sub-score computation. The suspended entry is not deleted or overwritten; both the original entry record and the dispute transaction record coexist permanently on the ledger in append-only fashion, preserving the full audit trail regardless of the dispute outcome.

[0125] During the provisional hold period, the node’s C3N Score is recomputed excluding the suspended entry. This recomputed provisional score is used for all trust-gated decisions — including validator selection, network routing, and smart contract execution — until the dispute is resolved. The provisional score is stored on-ledger as a distinct score record carrying a PROVISIONAL HOLD status flag, distinguishing it from the node’s normal certified score.

[0126] Dispute resolution proceeds through a configurable escalation tier system. The tier configuration is stored as a named, versioned ledger object specifying the number of arbitration tiers, the identity or role of the arbitrator at each tier, the decision period at each tier, and the vote threshold required for resolution at multi-member tiers. In one embodiment, the default tier configuration provides three tiers: Tier 1 is the subject node’s cluster manager; Tier 2 is a quorum of the node’s cluster peers; and Tier 3 is a governance vote of C3N network participants. If a tier’s arbitrator does not act within the configured decision period, the dispute automatically escalates to the next tier.3054252081.1Attorney Docket No. 95814-0021

[0127] A dispute resolution record is written to the distributed ledger upon resolution, specifying: the dispute outcome (UPHELD, REVERSED, or MODIFIED); the arbitration tier at which resolution occurred; the C3N address of the resolving arbitrator or quorum; the timestamp of resolution; and for REVERSED or MODIFIED outcomes, the corrected input value or the instruction to permanently exclude the contested entry. The original entry record, the dispute record, and the resolution record are linked by mutual hash references, forming a tamper-evident chain. Upon resolution, the provisional hold is lifted, the score is recomputed using the resolution outcome, and the updated certified score replaces the provisional score for all subsequent trustgated operations.

[0128] The Score Dispute Protocol architecture described herein is illustrated in FIG. 14.Regulatory Compliance Sub-Score

[0129] In various embodiments, the C3N platform supports a Regulatory Compliance SubScore (RCS): a certified sub-score dimension representing a node’s standing with respect to one or more jurisdiction-specific regulatory, sanctions, or legal compliance requirements. The RCS is designed for deployments in regulated sectors — including financial services, healthcare, and government — where legal standing is a material trust dimension that the base eight sub-scores do not capture.

[0130] RCS attestations are issued by C3N-designated regulatory authorities using the same on-ledger authority designation infrastructure that governs QUICK rule issuance and DISQUALIFYING CFR entry authorization. An entity authorized to issue RCS attestations for a given jurisdiction must appear in the on-ledger regulatory authority registry with a designation record specifying its C3N address, the jurisdiction it is authorized to certify, the entity that granted that authority, the timestamp of designation, and the applicable legal or regulatory basis. This architecture ensures that no new privileged actor class is introduced and that the compliance certification chain is fully auditable by any network participant.

[0131] Each RCS attestation is stored on the distributed ledger as a certified tier record — structurally parallel to the FCS tier representation — comprising: the subject node’s C3N address; the jurisdiction identifier; the issuing authority’s C3N address; the compliance tier value representing a defined standing level within the applicable regulatory framework; a certification3154252081.1Attorney Docket No. 95814-0021hash; and an expiry timestamp. The tier computation is performed by the issuing authority using whatever regulatory processes apply in the relevant jurisdiction; only the certified tier value — not the underlying compliance data — is written to the ledger. The RCS participates in CWV evaluation as an independently weighted dimension: a CWV may assign the RCS for a given jurisdiction a positive polarity and weight in deployment contexts where that jurisdiction’s regulatory standing is a trust requirement, and suppress it (polarity 0) in deployment contexts where it is irrelevant.

[0132] Sanctions screening outcomes are recorded as CFR entries under the Conduct Flag Registry architecture described above. Specifically, a confirmed sanctions hit issued by a designated authority is recorded as a DISQUALIFYING CFR entry, triggering the immediate hard-gate disqualification mechanism. This integration ensures that a sanctions finding produces an immediate automated technical effect on consensus participation and network routing access, without requiring the finding to propagate through composite scoring computation.

[0133] The RCS is an independently disclosable item under the Score Disclosure Rule Engine. The platform supports jurisdiction-scoped disclosure rules: a node may grant disclosure of its RCS for one jurisdiction to a specific counterparty without granting disclosure of its RCS for other jurisdictions. This granularity is achieved by treating each RCS jurisdiction id] as a separately named disclosable item within the disclosure rule engine’s per-item architecture. Score Event Bus

[0134] In various embodiments, the C3N platform implements a Score Event Bus (SEB): an event-driven mechanism that triggers immediate score recomputation and propagates the updated score to all trust-gated components whenever a defined material score event occurs. The SEB ensures that the PoR consensus mechanism and trust-gated routing infrastructure always operate on current score data, and that the maximum age of a cached score used in any trust-gated decision is a bounded, auditable quantity.

[0135] The SEB is governed by a materiality threshold configuration object stored as a named, versioned record on the distributed ledger. This object specifies, for each category of scoreaffecting event, whether that event type constitutes a material event triggering an immediate SEB recomputation cycle, or a routine update deferred to the next scheduled scoring epoch. Event3254252081.1Attorney Docket No. 95814-0021categories include: SLA failure recording, citizenship sub-score reduction, CFR entry creation, FCS tier change, RCS attestation update, TDWV version update, and SDP provisional hold application or resolution. The materiality thresholds are configurable by the network operator; in one embodiment, CFR DISQUALIFYING entries and FCS tier changes are defined as always-material, while minor SLA records and star ratings below a configurable individual weight threshold are deferred to the next epoch.

[0136] When a material event is recorded on the distributed ledger, the SEB triggers a score recomputation job for the affected node. Upon completion of the recomputation, the SEB generates a cache invalidation token: a signed ledger record specifying the affected node’s C3N address, the prior score value, the updated score value, the triggering event’s ledger hash, and a timestamp. The SEB broadcasts the invalidation token to all registered subscribers, which include the consensus module, the leader election module, and all fabric controllers that have cached a score for the affected node. Upon receipt, each subscriber atomically replaces its cached score value with the updated value and discards any pending routing or validator selection decisions that were computed using the prior score.

[0137]

[0075] The materiality threshold configuration object also specifies a propagation SLA for each material event type: the maximum elapsed time between ledger recording of the triggering event and confirmed receipt of the cache invalidation token by all registered subscribers. The propagation SLA is itself stored on the distributed ledger as part of the materiality threshold object, making the platform’s timeliness commitment an auditable, verifiable obligation rather than an implementation detail. Propagation SLA compliance is measured and recorded per-event in the SEB’s event log, which is an append-only ledger structure accessible to any authorized participant.

[0138] The Score Event Bus architecture described herein is illustrated in FIG. 13, alongside the Conduct Flag Registry and Score Dispute Protocol.

[0139] According to at least one embodiment, a system for managing trust-based distributed ledger operations, comprises: a distributed ledger configured to store, for each of a plurality of network nodes, a multi-dimensional trust score that cannot be manipulated or centrally controlled by any single entity; a trust score computation module configured to compute the multidimensional trust score as a weighted composite of a plurality of sub-scores drawn from three 3354252081.1Attorney Docket No. 95814-0021categories: a performance category comprising a service level agreement transaction history subscore and a citizenship sub-score; an opinion category comprising a manager approval rating subscore, an overall star rating sub-score, and a followed star rating sub-score; and a reputation category comprising a vouched-for points sub-score, an industry certifications sub-score, and a test scores sub-score; a consensus module configured to select validator nodes for block validation based on the multi-dimensional trust scores stored on the distributed ledger, wherein nodes having higher trust scores are preferentially selected as validators; a leader election module configured to designate, from a cluster of nodes, a leader node by: identifying the node with the highest multidimensional trust score as the leader; and in the event that two or more nodes share the highest trust score, designating the node with the earliest registration timestamp as the leader; and a network routing controller configured to condition the forwarding of network traffic between a source node and a destination node on the multi-dimensional trust scores of both the source node and the destination node satisfying a predetermined threshold.

[0140] According to at least one embodiment, the system described herein is further characterized whereby the trust score computation module is further configured to compute two additional sub-scores: (a) a financial capacity sub-score (FCS) derived entirely from native C3N platform data comprising wallet balances, digital asset holdings, and transaction history, stored on the distributed ledger as a certified tier integer representing a financial capacity band rather than a raw figure, wherein the tier certification is performed within the platform’s HSM-backed infrastructure; and (b) a network quality sub-score (NQS) computed as a graph-propagated weighted average over a connection registry of KYC / AML-verified C3N network members, wherein each connection’s contribution is weighted by that connection’s own financial capacity tier and organizational relationship to the scored entity, and wherein the NQS is stored on the distributed ledger as a certified tier integer.

[0141] According to at least one embodiment, the system described further comprises a context weight vector module configured to evaluate a contextual score for an entity by applying a named Context Weight Vector (CWV) stored on the distributed ledger, wherein the CWV assigns to each sub-score dimension a signed polarity value and a weight, wherein a polarity of +1 causes a higher dimension value to raise the contextual score, a polarity of 0 suppresses the dimension so3454252081.1Attorney Docket No. 95814-0021that it contributes neither positively nor negatively, and a polarity of -1 inverts the dimension’s contribution so that a lower dimension value raises the contextual score.

[0142] According to at least one embodiment, the system described herein is further characterized whereby the CWV further specifies, for one or more dimensions, a hard gate parameter comprising a threshold value and a gate polarity, wherein when the hard gate is active and the dimension value falls below the threshold for a positive-polarity gate, or exceeds the threshold for a negative-polarity gate, the contextual score is set to a floor value regardless of the values of all other dimensions, such that the hard gate functions as a binary disqualification mechanism rather than a weight reduction.

[0143] According to at least one embodiment, the system described further comprises a score disclosure rule engine configured to control access to each disclosable score item independently, wherein disclosable items include at minimum: a network quality sub-score tier, a network quality sub-score graph, a vouched-for sub-score, a vouched-for endorsement graph, a composite C3N Score, and each individually named base sub-score; wherein each disclosable item maintains an independent rule set that evaluates disclosure requests using a default-block policy and five specificity levels evaluated in order from most-specific to least-specific: QUICK rules, INDIVIDUAL rules, GROUP rules, CONTRACT rules, and BLOCKCHAIN rules; wherein a QUICK rule, once written, is irrevocable; and wherein the default disposition in the absence of any matching rule is to block disclosure.

[0144] According to at least one embodiment, the system described herein is further characterized whereby QUICK rules are writable by two and only two classes of actor: (a) the entity that owns the rule set, as an irrevocable exercise of self-sovereignty; and (b) infrastructurelevel regulatory authorities that are platform-defined, explicitly enumerated, and whose designation is itself an on-ledger record specifying the authority’s C3N address, the identity of the entity that elevated them, the timestamp of elevation, and the legal or regulatory basis for the designation; wherein any entity may inspect all QUICK rules written against their own disclosure rule sets, and wherein the set of regulatory authorities is itself auditable by any network participant.

[0145] According to at least one embodiment, the system described herein is further characterized whereby an authorized disclosure of the network quality sub-score graph causes the3554252081.1Attorney Docket No. 95814-0021system to traverse the entity’s connection registry and evaluate each connection’s own disclosure rule set against the same querying party, producing for each connection one of three output states: a full entry comprising the connection’s C3N address and financial capacity tier when the connection’s rule set permits graph disclosure; an anonymized entry comprising a redacted identifier and the financial capacity tier when the connection permits tier disclosure but not graph disclosure; and a redacted entry comprising only a placeholder when the connection permits neither tier nor graph disclosure; wherein no connection entries are omitted from the output, preserving graph size accuracy while applying each connection’s self-sovereign disclosure preferences.

[0146] According to at least one embodiment, a system for privacy-preserving network routing in a blockchain infrastructure comprises: a network node connector (NNC) associated with a cluster_c3n identifier in a Triple C3N Number hierarchy comprising a region_c3n component, a cluster_c3n component, and an entity _c3n component, wherein the NNC is configured to: receive network packets addressed using a Triple C3N Number; resolve the entity c3n component to an internal node address within a private cluster network using a local binding table; rewrite the source address of outbound packets to the cluster_c3n public identifier; assign a unique port to each translated session; and maintain a session translation table mapping assigned ports to originating internal entity _c3n values to enable reverse translation of inbound response packets.

[0147] According to at least one embodiment, the system described herein is further characterized whereby the NNC is one of a plurality of hierarchically nested NNCs forming a recursive translation stack in which each NNC rewrites packet source addresses to its own cluster_c3n identifier, such that the actual internal network address of a destination node is concealed from all NNCs except the innermost NNC in the stack.

[0148] According to at least one embodiment, the system described herein is further characterized whereby a cluster owner is authorized to configure the NNC to: bind entity _c3n identifiers to specific internal node addresses; define inter-cluster access policies; assign port ranges for different service types; and control the external visibility of entity _c3n records within the C3N routing fabric.3654252081.1Attorney Docket No. 95814-0021

[0149] According to at least one embodiment, the system described herein further comprises a time-decay weight vector module configured to: retrieve, for each entry in a time-stamped sub-score history array, a decay weight computed as a function of elapsed time since that entry was recorded, wherein the decay function type, decay rate parameter, and minimum weight floor are specified by a named Time-Decay Weight Vector (TDWV) object stored as a versioned record on the distributed ledger, and wherein each sub-score dimension may reference a distinct TDWV such that recency weighting is independently configurable per dimension; apply the decay weights as pre-multipliers to historical entries before the weighted average sub-score computation; enforce a minimum weight floor below which no entry’s weight is reduced; and, upon update of a TDWV version on the distributed ledger, generate a score recomputation event for all nodes whose sub-score arrays contain entries governed by the updated TDWV dimension and propagate updated scores to the consensus module and network routing controller with invalidation of prior cached values.

[0150] According to at least one embodiment, the system described herein further comprises a score stability computation module configured to: compute, for each node, a score stability index (SSI) derived from the population standard deviation of performance sub-score values recorded within a rolling time window whose boundaries are stored as a versioned record on the distributed ledger; normalize the SSI to a scale consistent with the other sub-score dimensions; store the SSI on the distributed ledger as a certified sub-score, wherein the SSI participates as an independently disclosable item in the score disclosure rule engine and as an independently weighted dimension in the context weight vector evaluation; and enforce, when a context weight vector specifies a hard gate parameter on the SSI dimension, categorical exclusion from the validator election candidate set of any node whose SSI falls below the configured threshold, regardless of that node’s composite multi-dimensional trust score.

[0151] According to at least one embodiment, the system described herein further comprises a rater independence module configured to: compute, for each input to an opinioncategory sub-score, a rater independence coefficient (RIC) derived from: (a) the normalized inverse of the shortest-path graph distance between the rater and the subject node within the C3N connection registry already maintained on the distributed ledger as defined in claim 2 for network quality sub-score graph traversal, and (b) a clique density penalty applied to raters whose local3754252081.1Attorney Docket No. 95814-0021clustering coefficient within the connection registry exceeds a configurable threshold stored as a versioned record on the distributed ledger; apply the RIC as a pre-weight multiplier to each opinion input before the weighted average computation, wherein the RIC-adjusted input value equals the raw input multiplied by the RIC for that rater-subject pair; publish, at each scoring epoch, a signed versioned record on the distributed ledger identifying the set of high-density subgraphs and their assigned discount factors, such that the clique identification and discounting basis is auditable by any network participant; and maintain a mutual endorsement registry on the distributed ledger tracking endorsement pairs in which both parties have endorsed each other, wherein entries in the mutual endorsement registry receive a configurable additional RIC discount.

[0152] According to at least one embodiment, the system described herein further comprises a conduct flag registry module configured to: maintain, on the distributed ledger, a Conduct Flag Registry (CFR) comprising severity-classified misconduct event records each associated with a specific node C3N address, wherein each record specifies a severity level of MINOR, MAJOR, or DISQUALIFYING, a structured event type classification, an issuing authority C3N address, and a resolution status; upon creation of a DISQUALIFYING CFR entry, immediately collapse the subject node’s composite multi-dimensional trust score and all contextual scores derived therefrom to a floor value, removing the node from the validator election candidate set and blocking network routing access, without requiring that effect to propagate through composite scoring computation; restrict issuance of DISQUALIFYING CFR entries to entities whose C3N address appears in the on-ledger regulatory authority registry with an explicit designation record specifying the authority to issue DISQUALIFYING entries, such that no new privileged actor class is introduced and the authorization chain for any DISQUALIFYING entry is fully traceable through the distributed ledger; and maintain each CFR entry as an independently disclosable item under the score disclosure rule engine.

[0153] According to at least one embodiment, the system described herein further comprises a score dispute protocol module configured to: receive a dispute transaction referencing a specific score input by its on-chain content hash; transition the referenced input to a DISPUTED state and apply a provisional hold suspending that entry from contribution to the subject node’s sub-score computation, wherein the original entry record and the dispute transaction record coexist permanently on the distributed ledger in append-only fashion; recompute the subject node’s multi-3854252081.1Attorney Docket No. 95814-0021dimensional trust score excluding the suspended entry and store the result on the distributed ledger as a provisional score record carrying a PROVISIONAL HOLD status flag, wherein the provisional score governs all trust-gated decisions during the hold period; escalate unresolved disputes through a configurable arbitration tier system whose tier count, arbitrator roles, decision periods, and vote thresholds are stored as a versioned record on the distributed ledger; and upon resolution, write a resolution record to the distributed ledger specifying the outcome, the resolving arbitrator, and any correction to the contested entry, and recompute and certify the node’s score using the resolution outcome.

[0154] According to at least one embodiment, the system described herein further comprises a regulatory compliance sub-score module configured to: store, on the distributed ledger, Regulatory Compliance Sub-Score (RCS) attestations issued by C3N-designated regulatory authorities, wherein each RCS attestation is stored as a certified tier record comprising a jurisdiction identifier, a compliance tier value representing a defined standing level, an issuing authority C3N address, a certification hash, and an expiry timestamp, and wherein no underlying compliance data other than the certified tier value is written to the ledger; restrict issuance of RCS attestations to entities appearing in the on-ledger regulatory authority registry with a designation record specifying authorization to certify the applicable jurisdiction, wherein authority to issue RCS attestations is restricted to entities recorded in an on-ledger regulatory authority registry — the same registry that governs issuance of DISQUALIFYING Conduct Flag entries and QUICK rule authority — comprising for each authorized entity: its C3N address, the jurisdictions for which it holds authorization, and a designation record written by a C3N platform governance transaction; enable context weight vectors to reference a named RCS dimension identified by jurisdiction identifier, such that a deployment context may assign the RCS a positive polarity and weight or suppress it entirely depending on whether that jurisdiction’s regulatory standing is relevant to the evaluation; record confirmed sanctions screening findings as DISQUALIFYING CFR entries under the conduct flag registry, thereby triggering the immediate hard-gate disqualification mechanism upon a sanctions hit; and treat each RCS:[jurisdiction_id] as a separately named disclosable item under the score disclosure rule engine, enabling jurisdiction-scoped disclosure control.3954252081.1Attorney Docket No. 95814-0021

[0155] According to at least one embodiment, the system described herein further comprises a score event bus module configured to: maintain, on the distributed ledger, a materiality threshold configuration object specifying for each category of score-affecting event whether that event type constitutes a material event triggering an immediate score recomputation cycle or a routine update deferred to the next scheduled scoring epoch, wherein the materiality threshold configuration object is a named, versioned ledger record; upon recording of a material event on the distributed ledger, trigger a score recomputation job for the affected node and, upon completion, generate a cache invalidation token comprising a signed ledger record specifying the affected node’s C3N address, the prior score value, the updated score value, the triggering event’s ledger hash, and a timestamp; broadcast the cache invalidation token to all registered subscribers including the consensus module, the leader election module, and all fabric controllers that have cached a score for the affected node, wherein each subscriber atomically replaces its cached score value with the updated value upon receipt; and enforce a propagation service level agreement specifying the maximum elapsed time between ledger recording of a material event and confirmed receipt of the cache invalidation token by all registered subscribers, wherein the propagation SLA is stored as part of the materiality threshold configuration object on the distributed ledger and compliance is recorded per-event in an append-only SEB event log accessible to authorized participants.

[0156] FIG. 1 illustrates a block diagram of an example of a machine 100 or system upon which any one or more of the techniques (e.g., methodologies) discussed herein may be performed. In other embodiments, the machine 100 may operate as a standalone device or may be connected (e.g., networked) to other machines. In a networked deployment, the machine 100 may operate in the capacity of a server machine, a client machine, or both in server-client network environments. The machine 100 may be a wearable device or any machine capable of executing instructions (sequential or otherwise) that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term “machine” shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein, such as cloud computing, software as a service (SaaS), or other computer cluster configurations.4054252081.1Attorney Docket No. 95814-0021

[0157] Examples, as described herein, may include or may operate on logic or a number of components, modules, or mechanisms. Modules are tangible entities (e.g., hardware) capable of performing specified operations when operating. A module includes hardware. In an example, the hardware may be specifically configured to carry out a specific operation (e.g., hardwired). In another example, the hardware may include configurable execution units (e.g., transistors, circuits, etc.) and a computer readable medium containing instructions where the instructions configure the execution units to carry out a specific operation when in operation. The configuring may occur under the direction of the executions units or a loading mechanism. Accordingly, the execution units are communicatively coupled to the computer-readable medium when the device is operating. In this example, the execution units may be a member of more than one module. For example, under operation, the execution units may be configured by a first set of instructions to implement a first module at one point in time and reconfigured by a second set of instructions to implement a second module at a second point in time.

[0158] The machine (e.g., computer system) 100 may include any combination of the illustrated components. For example, the machine 100 may include a hardware processor 102 (e.g., a central processing unit (CPU), a graphics processing unit (GPU), a tensor processing unit (TPU) including an artificial intelligence application-specific integrated circuit (ASIC), a hardware processor core, or any combination thereof), a main memory 104 and a static memory 106, some or all of which may communicate with each other via an interlink (e.g., bus) 108. The machine 100 may further include a power management device 132, a graphics display device 110, an alphanumeric input device 112 (e.g., a keyboard), and a user interface (UI) navigation device 114 (e.g., a mouse). In an example, the graphics display device 110, alphanumeric input device 112, and UI navigation device 114 may be a touch screen display. The machine 100 may additionally include a storage device (i.e., drive unit) 116, a signal generation device 118 (e.g., a data signal), a network interface device / transceiver 120 coupled to antenna(s) 130, and one or more sensors 128, such as a sound detecting sensor (e.g., a microphone), accelerometers, magnetometers, location sensors, and the like. The machine 100 may include an output controller 134, such as a serial (e.g., universal serial bus (USB), parallel, or other wired or wireless (e.g., infrared (IR), near field communication (NFC), etc.) connection to communicate with or control one or more peripheral devices (e.g., a printer, a card reader, other sensors, etc.)).4154252081.1Attorney Docket No. 95814-0021

[0159] The storage device 116 may include a machine readable medium 122 on which is stored one or more sets of data structures or instructions 124 (e.g., software) embodying or utilized by any one or more of the techniques or functions described herein. The instructions 124 may also reside, completely or at least partially, within the main memory 104, within the static memory 106, or within the hardware processor 102 during execution thereof by the machine 100. In an example, one or any combination of the hardware processor 102, the main memory 104, the static memory 106, or the storage device 116 may constitute machine-readable media.

[0160] While the machine-readable medium 122 is illustrated as a single medium, the term “machine-readable medium” may include a single medium or multiple media (e.g., a centralized or distributed database, and / or associated caches and servers) configured to store the one or more instructions 124.

[0161] Various embodiments may be implemented fully or partially in software and / or firmware. This software and / or firmware may take the form of instructions contained in or on a non-transitory computer-readable storage medium. Those instructions may then be read and executed by one or more processors to enable performance of the operations described herein. The instructions may be in any suitable form, such as but not limited to source code, compiled code, interpreted code, executable code, static code, dynamic code, and the like. Such a computer-readable medium may include any tangible non-transitory medium for storing information in a form readable by one or more computers, such as but not limited to read only memory (ROM); random access memory (RAM); magnetic disk storage media; optical storage media; a flash memory, etc.

[0162] The term “machine-readable medium” may include any medium that is capable of storing, encoding, or carrying instructions for execution by the machine 100 and that cause the machine 100 to perform any one or more of the techniques of the present disclosure, or that is capable of storing, encoding, or carrying data structures used by or associated with such instructions. Non-limiting machine-readable medium examples may include solid-state memories and optical and magnetic media. In an example, a massed machine-readable medium includes a machine-readable medium with a plurality of particles having resting mass. Specific examples of massed machine-readable media may include non-volatile memory, such as semiconductor4254252081.1Attorney Docket No. 95814-0021memory devices (e.g., electrically programmable read-only memory (EPROM), or electrically erasable programmable read-only memory (EEPROM)) and flash memory devices; magnetic disks, such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD- ROM disks.

[0163] The instructions 124 may further be transmitted or received over a communications network 126 using a transmission medium via the network interface device / transceiver 120 utilizing any one of a number of transfer protocols (e.g., frame relay, internet protocol (IP), transmission control protocol (TCP), user datagram protocol (UDP), hypertext transfer protocol (HTTP), etc.). Example communications networks may include DOCSIS, fiber optic, a local area network (LAN), a wide area network (WAN), a packet data network (e.g., the Internet), mobile telephone networks (e.g., cellular networks), plain old telephone (POTS) networks, wireless data networks (e.g., Institute of Electrical and Electronics Engineers (IEEE) 802.1 family of standards known as Wi-Fi®, IEEE 802.16 family of standards known as WiMax®), IEEE 802.15.4 family of standards, and peer-to-peer (P2P) networks, among others. In an example, the network interface device / transceiver 120 may include one or more physical jacks (e.g., Ethernet, coaxial, or phone jacks) or one or more antennas to connect to the communications network 126. In an example, the network interface device / transceiver 120 may include a plurality of antennas to wirelessly communicate using at least one of single-input multiple-output (SIMO), multiple-input multipleoutput (MIMO), or multiple-input single-output (MISO) techniques. The term “transmission medium” shall be taken to include any intangible medium that is capable of storing, encoding, or carrying instructions for execution by the machine 100 and includes digital or analog communications signals or other intangible media to facilitate communication of such software.

[0164] The operations and processes described and shown above may be carried out or performed in any suitable order as desired in various implementations. Additionally, in certain implementations, at least a portion of the operations may be carried out in parallel. Furthermore, in certain implementations, less than or more than the operations described may be performed.

[0165] The word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments. The terms “computing device,” “user4354252081.1Attorney Docket No. 95814-0021device,” “communication station,” “station,” “handheld device,” “mobile device,” “wireless device” and “user equipment” (UE) as used herein refers to a wireless communication device such as a cable box, a wearable smart device, cellular telephone, a smartphone, a tablet, a netbook, a wireless terminal, a laptop computer, a femtocell, a high data rate (HDR) subscriber station, an access point, a printer, a point of sale device, an access terminal, or other personal communication system (PCS) device. The device may be either mobile or stationary.

[0166] As used within this document, the term “communicate” is intended to include transmitting, or receiving, or both transmitting and receiving. This may be particularly useful in claims when describing the organization of data that is being transmitted by one device and received by another, but only the functionality of one of those devices is required to infringe the claim. Similarly, the bidirectional exchange of data between two devices (both devices transmit and receive during the exchange) may be described as “communicating,” when only the functionality of one of those devices is being claimed. The term “communicating” as used herein with respect to a wireless communication signal includes transmitting the wireless communication signal and / or receiving the wireless communication signal. For example, a wireless communication unit, which is capable of communicating a wireless communication signal, may include a wireless transmitter to transmit the wireless communication signal to at least one other wireless communication unit, and / or a wireless communication receiver to receive the wireless communication signal from at least one other wireless communication unit.

[0167] As used herein, unless otherwise specified, the use of the ordinal adjectives “first,” “second,” “third,” etc., to describe a common object, merely indicates that different instances of like objects are being referred to and are not intended to imply that the objects so described must be in a given sequence, either temporally, spatially, in ranking, or in any other manner.

[0168] Some embodiments may be used in conjunction with various devices and systems, for example, a wearable smart device, a personal computer (PC), a desktop computer, a mobile computer, a laptop computer, a notebook computer, a tablet computer, a server computer, a handheld computer, a handheld device, a personal digital assistant (PDA) device, a handheld PDA device, an on-board device, an off-board device, a hybrid device, a vehicular device, a non-vehicular device, a mobile or portable device, a consumer device, a non-mobile or non-portable4454252081.1Attorney Docket No. 95814-0021device, a wireless communication station, a wireless communication device, a wireless access point (AP), a wired or wireless router, a wired or wireless modem, a video device, an audio device, an audio-video (A / V) device, a wired or wireless network, a wireless area network, a wireless video area network (WVAN), a local area network (LAN), a wireless LAN (WLAN), a personal area network (PAN), a wireless PAN (WPAN), and the like.

[0169] Some embodiments may be used in conjunction with one way and / or two-way radio communication systems, cellular radio-tel ephone communication systems, a mobile phone, a cellular telephone, a wireless telephone, a personal communication system (PCS) device, a PDA device which incorporates a wireless communication device, a mobile or portable global positioning system (GPS) device, a device which incorporates a GPS receiver or transceiver or chip, a device which incorporates an RFID element or chip, a multiple input multiple output (MIMO) transceiver or device, a single input multiple output (SIMO) transceiver or device, a multiple input single output (MISO) transceiver or device, a device having one or more internal antennas and / or external antennas, digital video broadcast (DVB) devices or systems, multistandard radio devices or systems, a wired or wireless handheld device, e.g., a smartphone, a wireless application protocol (WAP) device, or the like.

[0170] Some embodiments may be used in conjunction with one or more types of wireless communication signals and / or systems following one or more wireless communication protocols, for example, DOCSIS, radio frequency (RF), infrared (IR), frequency-division multiplexing (FDM), orthogonal FDM (OFDM), time-division multiplexing (TDM), time-division multiple access (TDMA), extended TDMA (E-TDMA), general packet radio service (GPRS), extended GPRS, code-division multiple access (CDMA), wideband CDMA (WCDMA), CDMA 2000, single-carrier CDMA, multi-carrier CDMA, multi-carrier modulation (MDM), discrete multi-tone (DMT), Bluetooth®, global positioning system (GPS), Wi-Fi, Wi-Max, ZigBee, ultra-wideband (UWB), global system for mobile communications (GSM), 2G, 2.5G, 3G, 3.5G, 4G, fifth generation (5G) mobile networks, 3GPP, long term evolution (LTE), LTE advanced, enhanced data rates for GSM Evolution (EDGE), or the like. Other embodiments may be used in various other devices, systems, and / or networks.4554252081.1Attorney Docket No. 95814-0021

[0171] Embodiments according to the disclosure are in particular disclosed in the attached claims directed to a method, a storage medium, a device and a computer program product, wherein any feature mentioned in one claim category, e.g., method, can be claimed in another claim category, e.g., system, as well. The dependencies or references back in the attached claims are chosen for formal reasons only. However, any subject matter resulting from a deliberate reference back to any previous claims (in particular multiple dependencies) can be claimed as well, so that any combination of claims and the features thereof are disclosed and can be claimed regardless of the dependencies chosen in the attached claims. The subject-matter which can be claimed comprises not only the combinations of features as set out in the attached claims but also any other combination of features in the claims, wherein each feature mentioned in the claims can be combined with any other feature or combination of other features in the claims. Furthermore, any of the embodiments and features described or depicted herein can be claimed in a separate claim and / or in any combination with any embodiment or feature described or depicted herein or with any of the features of the attached claims.

[0172] The foregoing description of one or more implementations provides illustration and description, but is not intended to be exhaustive or to limit the scope of embodiments to the precise form disclosed. Modifications and variations are possible in light of the above teachings or may be acquired from practice of various embodiments.

[0173] Certain aspects of the disclosure are described above with reference to block and flow diagrams of systems, methods, apparatuses, and / or computer program products according to various implementations. It will be understood that one or more blocks of the block diagrams and flow diagrams, and combinations of blocks in the block diagrams and the flow diagrams, respectively, may be implemented by computer-executable program instructions. Likewise, some blocks of the block diagrams and flow diagrams may not necessarily need to be performed in the order presented, or may not necessarily need to be performed at all, according to some implementations.

[0174] These computer-executable program instructions may be loaded onto a specialpurpose computer or other particular machine, a processor, or other programmable data processing apparatus to produce a particular machine, such that the instructions that execute on the computer,4654252081.1Attorney Docket No. 95814-0021processor, or other programmable data processing apparatus create means for implementing one or more functions specified in the flow diagram block or blocks. These computer program instructions may also be stored in a computer-readable storage media or memory that may direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable storage media produce an article of manufacture including instruction means that implement one or more functions specified in the flow diagram block or blocks. As an example, certain implementations may provide for a computer program product, comprising a computer-readable storage medium having a computer- readable program code or program instructions implemented therein, said computer-readable program code adapted to be executed to implement one or more functions specified in the flow diagram block or blocks. The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational elements or steps to be performed on the computer or other programmable apparatus to produce a computer- implemented process such that the instructions that execute on the computer or other programmable apparatus provide elements or steps for implementing the functions specified in the flow diagram block or blocks.

[0175] Accordingly, blocks of the block diagrams and flow diagrams support combinations of means for performing the specified functions, combinations of elements or steps for performing the specified functions and program instruction means for performing the specified functions. It will also be understood that each block of the block diagrams and flow diagrams, and combinations of blocks in the block diagrams and flow diagrams, may be implemented by specialpurpose, hardware-based computer systems that perform the specified functions, elements or steps, or combinations of special-purpose hardware and computer instructions.

[0176] Conditional language, such as, among others, “can,” “could,” “might,” or “may,” unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain implementations could include, while other implementations do not include, certain features, elements, and / or operations. Thus, such conditional language is not generally intended to imply that features, elements, and / or operations are in any way required for one or more implementations or that one or more implementations necessarily include logic for deciding, with or without user input or prompting, whether these4754252081.1Attorney Docket No. 95814-0021features, elements, and / or operations are included or are to be performed in any particular implementation.

[0177] Many modifications and other implementations of the disclosure set forth herein will be apparent having the benefit of the teachings presented in the foregoing descriptions and the associated drawings. Therefore, it is to be understood that the disclosure is not to be limited to the specific implementations disclosed and that modifications and other implementations are intended to be included within the scope of the appended claims. Although specific terms are employed herein, they are used in a generic and descriptive sense only and not for purposes of limitation.

[0178] All references, including publications, patent applications, and patents, cited are hereby incorporated by reference to the same extent as if each reference were individually and specifically indicated to be incorporated by reference and were set forth in its entirety.4854252081.1

Claims

Attorney Docket No. 95814-0021CLAIMS WHAT IS CLAIMED IS:

1. A system for implementing a smart contract enabled blockchain platform, comprising:a blockchain infrastructure layer configured to provide network routing, resource management, service discovery, container orchestration, risk rating services, node management, chain management, and messaging services, wherein the blockchain infrastructure layer implements a Proof-of-Reputation (PoR) consensus mechanism in which validator nodes are selected based on a multi-dimensional trust score comprising a weighted composite of sub-scores reflecting service level agreement history, citizenship, peer ratings, vouched-for endorsements, industry certifications, and competency assessments, wherein the multi-dimensional trust score is stored on a distributed ledger not controllable by any single entity;a plurality of blockchain interfaces defining operations for blockchain types, the plurality of blockchain interfaces being software constructs that indicate capabilities of the plurality of blockchain interfaces but not how the capabilities are implemented;an integrated development environment configured to receive rules or logic from an entity; anda smart contract engine configured to generate concrete smart contract implementations based on the received rules or logic, wherein the concrete smart contract implementations implement the capabilities indicated by the plurality of blockchain interfaces.

2. The system of claim 1, wherein the plurality of blockchain interfaces includes at least one of: an identity management interface, a financial interface, an asset interface, a governance interface, a messaging interface, and a utility interface.

3. The system of claim 2, wherein the asset interface defines operations for at least one of: real world assets, royalties, identity tokens, and non-fungible tokens (NFTs).4954252081.1Attorney Docket No. 95814-00214. The system of claim 2, wherein the governance interface defines operations for at least one of: voting, treasury management, and proposal execution.

5. The system of claim 1, wherein the blockchain infrastructure layer further comprises a software-defined networking component configured to establish tunnels between network nodes for smart contract execution.

6. The system of claim 5, wherein the software-defined networking component comprises a fabric controller configured to provide routing decisions to data plane devices using a pull-based routing approach, wherein the data plane devices request routes when needed rather than maintaining complete routing tables.

7. The system of claim 1, wherein the blockchain infrastructure layer implements a Proof-of-Reputation (PoR) consensus mechanism in which validator nodes are selected based on a multidimensional trust score comprising a weighted composite of eight sub-scores drawn from three categories: a performance category comprising a service level agreement transaction history subscore and a citizenship sub-score; an opinion category comprising a manager approval rating subscore, an overall star rating sub-score, and a followed star rating sub-score; and a reputation category comprising a vouched-for points sub-score, an industry certifications sub-score, and a test scores sub-score.

8. The system of claim 1, wherein the blockchain infrastructure layer is configured to support a plurality of distinct blockchains, each blockchain having respective smart contract implementations for the plurality of blockchain interfaces.5054252081.1Attorney Docket No. 95814-00219. A method for implementing a smart contract enabled blockchain platform, the method comprising:providing, by a blockchain infrastructure layer, network routing, resource management, service discovery, container orchestration, risk rating services, node management, chain management, and messaging services, wherein the blockchain infrastructure layer implements a Proof-of-Reputation (PoR) consensus mechanism in which validator nodes are selected based on a multi-dimensional trust score comprising a weighted composite of sub-scores reflecting service level agreement history, citizenship, peer ratings, vouched-for endorsements, industry certifications, and competency assessments, wherein the multi-dimensional trust score is stored on a distributed ledger not controllable by any single entity;defining, by a plurality of blockchain interfaces, operations for blockchain types, the plurality of blockchain interfaces being software constructs that indicate capabilities of the plurality of blockchain interfaces but not how the capabilities are implemented;receiving, by an integrated development environment, rules or logic from an entity; andgenerating, by a smart contract engine, concrete smart contract implementations based on the received rules or logic, wherein the concrete smart contract implementations implement the capabilities indicated by the plurality of blockchain interfaces.

10. The method of claim 9, wherein the blockchain infrastructure layer further comprises a software-defined networking component configured to establish tunnels between network nodes for smart contract execution.

11. The method of claim 9, wherein the software-defined networking component comprises a fabric controller configured to provide routing decisions to data plane devices using a pull-based5154252081.1Attorney Docket No. 95814-0021routing approach, wherein the data plane devices request routes when needed rather than maintaining complete routing tables.

12. The method of claim 9, wherein the blockchain infrastructure layer implements a Proof-of-Reputation (PoR) consensus mechanism in which validator nodes are selected based on a multidimensional trust score comprising a weighted composite of eight sub-scores drawn from three categories: a performance category comprising a service level agreement transaction history subscore and a citizenship sub-score; an opinion category comprising a manager approval rating subscore, an overall star rating sub-score, and a followed star rating sub-score; and a reputation category comprising a vouched-for points sub-score, an industry certifications sub-score, and a test scores sub-score.

13. The method of claim 9, wherein the blockchain infrastructure layer is configured to support a plurality of distinct blockchains, each blockchain having respective smart contract implementations for the plurality of blockchain interfaces.

14. A non-transitory computer-readable medium storing executable instructions that, as a result of execution by one or more processors of a computer system, cause the computer system to:provide a blockchain infrastructure layer for network routing, resource management, service discovery, container orchestration, risk rating services, node management, chain management, and messaging services, wherein the blockchain infrastructure layer implements a Proof-of-Reputation (PoR) consensus mechanism in which validator nodes are selected based on a multi-dimensional trust score comprising a weighted composite of sub-scores reflecting service level agreement history, citizenship, peer ratings, vouched-for endorsements, industry certifications, and competency assessments, wherein the multi-dimensional trust score is stored on a distributed ledger not controllable by any single entity;5254252081.1Attorney Docket No. 95814-0021define, for a plurality of blockchain interfaces, operations for blockchain types, the plurality of blockchain interfaces being software constructs that indicate capabilities of the plurality of blockchain interfaces but not how the capabilities are implemented;receive, by an integrated development environment, rules or logic from an entity; andgenerate, by a smart contract engine, concrete smart contract implementations based on the received rules or logic, wherein the concrete smart contract implementations implement the capabilities indicated by the plurality of blockchain interfaces.

15. The non-transitory computer-readable medium of claim 14, wherein the blockchain infrastructure layer is implemented as a C3N blockchain infrastructure.

16. A system for trust-gated network routing in a blockchain infrastructure, comprising:a fabric controller configured to: receive a registration request associating a first host and a second host; store a route between the first host and the second host in a local cache; request, from a blockchain-backed rating service, trust scores for the first host and the second host, wherein the blockchain-backed rating service stores trust scores on a distributed ledger not controllable by any single entity; store the trust scores for the first host and the second host in the local cache; and respond to a route request from a data plane switch by returning the cached route only if the trust scores of both the first host and the second host satisfy a predetermined threshold; anda data plane switch configured to: receive a connection request from a source endpoint seeking to reach a destination endpoint; forward a route request to the fabric controller; upon receiving a route from the fabric controller, encapsulate a frame into a Layer 3 packet and transmit the packet via a tunnel to a second data plane switch associated with the destination endpoint; and enforce access control policies based on network identifiers and tags associated with the returned route.5354252081.1Attorney Docket No. 95814-002117. The system of claim 1, wherein the smart contract engine is further configured to select a worker node to execute a smart contract from a plurality of available nodes based at least in part on a trust score of the worker node, wherein the trust score is stored on a distributed ledger not controllable by any single entity.

18. The system of claim 1, wherein each smart contract managed by the smart contract engine is identified by a content-addressed hash identifier computed as a cryptographic hash of the smart contract’ s contents, such that the smart contract may be retrieved from any distributed storage node that holds a copy of the content corresponding to the hash.

19. The system of claim 1, wherein the smart contract engine is further configured to store a smart contract in an encrypted form in a distributed file system, wherein a public key of each contracting party is stored alongside the smart contract, and wherein either contracting party may decrypt the smart contract using Shamir’s Secret Sharing Algorithm without the unilateral cooperation of any single party.

20. The system of claim 7, wherein the weighted composite of eight sub-scores comprises: a service level agreement transaction history sub-score, a citizenship sub-score, a manager approval rating sub-score, an overall star rating sub-score, a followed star rating sub-score, a vouched-for points sub-score, an industry certifications sub-score, and a test scores sub-score.

21. The system of claim 6, wherein the fabric controller is configured to return a route to a requesting data plane device only if trust scores for both a source host and a destination host satisfy a threshold score, and to withhold the route if the trust score of either the source host or the destination host fails to satisfy the threshold score.5454252081.1Attorney Docket No. 95814-002122. The system of claim 7, wherein the Proof-of-Reputation consensus mechanism further comprises a leader election protocol in which: the node with the highest trust score in a cluster is designated the leader node; in the event of a tie in trust scores, the node with the earliest registration timestamp is designated the leader node; and all nodes in the cluster are provided with the trust scores of all other nodes in the cluster to enable distributed tie-resolution without a central coordinator.

23. The system of claim 1, wherein the smart contract engine is further configured to monitor transfer of funds during smart contract execution and to commit a verified transaction to the distributed ledger only after funds have been successfully transferred from an initiating party’s account to a receiving party’s account, preventing partial execution states from being recorded on the distributed ledger.5554252081.1

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