88 results about "Oracle machine" patented technology

The invention relates to the technical field of data processing, provides a multi-node carbon emission intelligent contract verification method based on a block chain, and aims to solve the problems that data verification in an existing carbon asset transaction system is non-transparent, high in trust cost and difficult to adapt to policy changes. Distributed storage and dynamic verification of data are realized by constructing a hierarchical block chain architecture, the data are collected by using edge computing nodes, and third-party verification data are obtained through an oracle machine node cluster. The dynamic rule engine monitors data changes in real time, triggers a multi-stage verification process, and improves the data accuracy. And meanwhile, an improved Byzantine fault-tolerant mechanism is adopted to reach a consensus, and the system has the functions of strategy dynamic updating and security enhancement, so that the flexibility and security of the system are improved. According to the method, multi-party consensus and real-time verification of the carbon emission data are realized, trust cost of cooperation among enterprises is reduced, and healthy development of a carbon emission permit trading market is promoted.

AI neural networks are integrated with distributed ledger technology (DLT), including the integration of decentralized oracles, to enhance the functionality, security, and efficiency of systems. The integration incorporates several components and methods comprising novel neural network architectures, data preprocessing techniques, DLT integration approaches, privacy and security measures, consensus mechanisms, and others. The invention enables the development of neural smart contracts, neural consensus algorithms, dynamic neural network training, neural network optimization techniques, hybrid DLT architectures, neural network interpretability methods, and reinforcement learning for neural smart contract execution. By integrating decentralized oracles into the system, the invention has the capability to further enhance the reliability, accuracy, and diversity of data used within the DLT, improving transaction validation, consensus mechanisms, and overall system performance.

The invention discloses an efficient and compact key packaging, encryption and decryption method based on NTRU. The invention belongs to the technical field of lattice passwords, and particularly relates to an NTRU-based secret key packaging, encrypting and decrypting method with scalable ciphertext compression and balanced performance. According to the method, a public key compression and scaling ciphertext compression technology is provided for an NTRU password system, only one polynomial is needed in the encryption and decryption process, and the technology is also suitable for other password schemes based on NTRU. The method has the advantages of being shorter in ciphertext size, more flexible in parameter selection, capable of proving security under classical and quantum random oracle models, tighter in theoretical security protocol advantage, higher in known attack resistance, efficient in implementation, negligible in error rate and the like.

The invention discloses a power data management method based on a block chain, and relates to the field of block chains, and the method comprises the steps: initiating a data request; randomly selecting a preset number of oracle machine nodes; segmenting a private key of the request task into a plurality of parts by adopting a threshold key segmentation method; acquiring requested power data from an external data source; verifying the obtained power data; a Byzantine fault-tolerant consensus mechanism is adopted to achieve a consensus for the power data; signing the verified power data through a threshold signature method; the oracle machine management contract performs aggregation verification on the received signature data; the oracle machine management contract returns the power data passing the aggregation verification to the intelligent contract of the data requester; the intelligent contract of the data requester obtains the returned power data through an event monitoring mechanism, and executes corresponding business logic and state updating according to the power data; aiming at the low fault-tolerant capability of an oracle machine in power data management in the prior art, the fault-tolerant capability of the system is improved.

The invention discloses an application method and device of a battery model management iteration system based on federated learning and block chain verification, and relates to the field of block chain energy storage management, and the method comprises the steps: deploying an intelligent contract on a block chain to publish a federated learning task, and initializing a global model; each participant uses a private data local training model, encrypts and uploads the private data local training model to a central coordination server for security aggregation; submitting the aggregated global model to a block chain verification layer, and automatically evaluating the performance and recording a result by the smart contract; the verified model is deployed to an actual scene for battery state prediction; collecting actual operation data of the battery through an oracle machine feedback network, and feeding back the data to a chain; and the intelligent contract incentive engine automatically re-evaluates the performance of the model according to feedback data, distributes rewards, and iteratively optimizes a loop. According to the method, the problem that data islands exist in key parameter prediction models such as the state of health and the remaining service life of the battery is solved, and the credibility and the sustainable evolution ability of the prediction models are enhanced.

The invention relates to a block chain on-chain and off-chain linkage query method and system based on a decentralized oracle machine, and the method comprises the steps: obtaining to-be-stored multi-modal data, storing the multi-modal data in an off-chain manner, obtaining a data abstract through abstract calculation, and obtaining a label and a value of the label through information labeling; constructing a time index; storing the time index, the label and the value of the label in a storage contract deployed on a chain; the storage under the chain synchronizes the data abstract and the storage address to an oracle contract deployed on the chain, and the oracle contract is subscribed by a decentralized oracle network; the storage contract responds to the user query and is sent to the oracle contract, and the nodes in the decentralized oracle network generate integrity proof based on the subscribed user query; and the decentralized oracle machine network aggregates the digital signatures of the nodes to obtain multiple signatures reaching a threshold value, and sends the original data, the multiple signatures and the integrity proof corresponding to the user query to the user to realize the block chain up-chain and down-chain linkage query.

A system and method for providing a randomness function to a smart contact on a decentralized network. An oracle receives a request for at least one random value to be supplied to a smart contract executing on a decentralized network, the request including a seed. The oracle generates the at least one random value based on the seed, and a secret key associated with the oracle, wherein the oracle is identified on the decentralized network by a public key associated with the secret key. The oracle generates a cryptographic proof based on the at least one random value and the public key and sends the at least one random value and the cryptographic proof to the decentralized network, whereby the proof, and thus the randomness of the at least one random value, can be verified.

The invention is suitable for the technical field of data processing, and particularly relates to a financial data processing and classification method, system and equipment based on verifiable computing, and the method comprises the steps: obtaining on-chain transaction data verified by a block chain consensus node storage and risk-related index data verified by an under-chain oracle machine; the problems that the authenticity of traditional financial data is difficult to verify and the data is split are solved; calling a risk assessment model through an intelligent contract deployed on a block chain, and placing an assessment process in a decentralized block chain network; performing verifiable calculation through an intelligent contract to determine a total performance score and a risk index, and realizing whole-course tracing and verification of a calculation process by utilizing the characteristics of verifiable calculation of a block chain; the total performance score and the risk index are stored in the block chain as non-tampering records, and the risk rating groups are automatically divided according to the fixed rating rule on the chain through the smart contract, so that the authenticity, objectivity, verifiability and fairness of financial data processing are guaranteed.

The invention relates to the technical field of oracle machines, and provides an oracle machine implementation method and system for protecting multi-source data privacy and source authenticity, and the method comprises the steps: integrating the data of each data source through a credible center, and establishing communication between a verifier, a certifier and each data source; the certifier calls a query template provided by the verifier and generates a query of each data source and a query of each data source in combination with the private parameters, the certifier and the verifier perform calculation through two parties to generate an MAC value of the query, and encryption operation is performed on the query of each data source in combination with a held session key share; each data source generates encrypted and authenticated multi-source data based on the encrypted query; after the certifier carries out commitment operation on the verifier, the MAC key is recovered, and the multi-source data subjected to encryption authentication are decrypted and verified to obtain the multi-source data; and for communication data, the source authenticity is proved through zero-knowledge proof. And the complexity of multi-data source key management and use is reduced.

The present disclosure describes various methods, systems, and storage medium for training a language model to obtain an iterative Nash policy optimized (INPO) language model. The method includes initializing a first language model by a reference language model; for N-th iteration with N starting from 1 to M, generating a plurality of responses using the N-th language model for each prompt in a plurality of prompts, and constructing a preference dataset using a preference oracle based on the plurality of responses for each prompt, wherein the preference dataset comprises a winning response and a losing response; training the N-th language model to obtain a (N+1)-th language model by minimizing a value of an INPO function for all preference dataset for the plurality of prompts, wherein the INPO function comprises an expectation term, a regularization term, and a modification term; and outputting the (M+1)-th language model.

The invention provides a data transmission method, a block chain oracle system, equipment and a medium. The block chain oracle system comprises an oracle contract module, a data signature aggregator, a plurality of first oracles and a data interface. The data transmission method comprises the following steps: an oracle machine contract module receives a data transmission request, and broadcasts and notifies each first oracle machine to obtain data from a data interface according to the data transmission request; the data signature aggregator obtains to-be-transmitted data corresponding to the data transmission request according to data obtained by the first oracle machine; sending the to-be-transmitted data to first oracle machines of which the number is not less than a preset threshold number for signature, and aggregating to obtain the to-be-transmitted data containing an information signature; and sending the to-be-transmitted data containing the information signature to an oracle contract module for verification to obtain a verification result, and transmitting the to-be-transmitted data to a receiver according to the verification result. According to the scheme of the application, the security of data transmission in the block chain oracle system can be improved.

Techniques for fast smart contract processing and validation. A C3N smart contract may be written in a high-level programming language such as Go rather than a domain-specific language (DSL) for smart contracts that is difficult to learn and utilize correctly. The smart contract may support a predefined list of C3N libraries, including APIs for accessing components within a C3N containerized environment. The smart contract may natively support access to oracles and data external to the C3N blockchain. The C3N smart contact may be deployed as source code or executable code for one or more target architectures. Such executable code may be run directly on the target architectures without additional compilation or interpretation. Validator nodes can verify correct execution of C3N smart contracts through unit tests.

A system and method in which a network of offchain oracle nodes are used to provide dynamic information to consuming smart contracts in a decentralized computing environment. The off-chain oracle network and a corresponding protocol reduces the likelihood of damage from rogue oracles acting in concert. Periodically, the oracle nodes, jointly and in concert, run the protocol to sign a report containing observations from many of the oracles in the network. The report is transmitted to a smart contract C running on a DLT. The smart contract C can validate the report, pay each oracle node that contributed an observation to the report and expose the median, or other calculated value, of the reported values to the on-chain consuming smart contracts.

The invention relates to the technical field of internetwork settlement, in particular to an account checking method and device based on a block chain oracle machine and secure multi-party computing, computer equipment, a non-temporary computer readable storage medium and a computer program product. According to the method, a credible, automatic and transparent scene on a chain is provided by adopting a smart contract based on a block chain, the contradiction between account checking data privacy and verifiability among operators is solved through privacy perception by adopting secure multi-party calculation, and meanwhile, reverse operation is performed on an oracle machine; complex calculation in the smart contract is put into an out-of-chain oracle machine operation, and finally a difference vector set of account checking is accurately obtained, and then whether internetwork settlement continues to be carried out is judged. On the premise of guaranteeing the privacy, credibility and safety of the account checking data through cooperation of the three, the defects that the account checking efficiency is low, the account checking process is not supervised, and the account checking result is not subjected to closed-loop feedback are overcome.

The invention discloses a price query method and device based on an oracle machine, electronic equipment and a storage medium, and relates to the technical field of block chains or other related technical fields, and the method comprises the steps: receiving a financial transaction request initiated by a user side based on a block chain interaction interface, and determining a to-be-queried target object and a target timestamp; calling a data interface of an oracle machine, and determining a to-be-queried initial data period range; carrying out iterative calculation on the basis of the initial data period range by adopting a dichotomy method, and reducing the to-be-queried data period range until a target data period is obtained; and traversing the historical price data in the target data period, querying target historical price data corresponding to the target timestamp, and sending the target historical price data to the block chain interaction interface. According to the method and the device, the technical problem of relatively low efficiency of querying the price by traversing the data flow in the oracle machine in the block chain in the related technology is solved.

This invention provides a real-time intelligent teaching system and method for panoramic driving training, relating to the field of driving training technology. It includes: a task and credential module, an execution and causal reversal module, a reconstruction and snapshot module, a penalty and reputation feedback module, and an audit and compliance module. The system generates oracle credentials bound to an initial success probability estimate through an oracle network; it uses a verifiable delay function to set a time window for completing the signature, enabling locking, unlocking, or rollback of the execution witness; it supports concurrent and symmetric scheduling of mirrored tasks; it calculates staking penalties and updates reputation based on the initial success probability using a convex function mechanism; and finally, it writes all process data into an immutable audit chain and generates zero-knowledge proof compliance credentials for verification by regulatory agencies.

The invention relates to a cross-platform-based digital copyright transaction method, device and system and a medium, and belongs to the technical field of distributed digital asset management, cross-chain communication protocols, smart contracts and distributed computing. The method comprises the following steps: generating a digital fingerprint through a multi-mode hash algorithm, and storing digital copyright information in an IPFS network in a distributed manner; accessing a CoinGecko TM API (Application Program Interface) by adopting an oracle machine to obtain a market index in real time, and dynamically adjusting the pricing of copyright assets according to the market index and the copyright information; cross-chain asset transfer is realized on the basis of a Polkadot XCMP protocol; graph Protocol is integrated to construct a real-time risk control network, and real-time monitoring and risk assessment of digital copyright transactions are realized; and transaction settlement is automatically executed through the smart contract. According to the invention, the problems of high transaction barrier, rigid pricing mechanism, prominent security risk, difficulty in cross-chain collaboration and the like in the existing digital copyright transaction platform are solved, and efficient circulation and secure transaction of digital copyright assets are realized.

A method may include: receiving, by a smart contract, a request for a random number and a randomness seed from a user; deploying the request as a transaction that is written on a first block in the decentralized ledger; generating, by an oracle, a plurality of pseudorandom quantum circuits using the randomness seed; providing the plurality of pseudorandom quantum circuits to a quantum randomness source, wherein the quantum randomness source executes the quantum circuits and returns a sequence of random bits to the oracle; writing the sequence of random bits to a new block in the decentralized ledger; hashing the sequence of random bits and a block hash for the new block; and returning the hash of the sequence of random bits and the block hash to the user computer program, wherein the user consumes hash of the sequence of random bits and the block hash.

The invention relates to the technical field of tax data processing, in particular to a blockchain-based tax audit management system, which comprises a semantic business activity acquisition module for capturing business data from an operating system of a factoring business participant, converting the business data into a semantic unit and storing the semantic unit in a blockchain; the dynamic tax rule evolution module optimizes a tax payment obligation identification model through a federated learning framework; the tax payment event association module is integrated with an oracle machine network to construct a tax payment event atlas; the cash flow tracing and sharing module adopts an ant colony optimization algorithm to generate a cash flow incidence matrix; the auditing deduction and feedback module generates a calibration signal through simulation deduction and feeds the calibration signal back to the rule evolution module. All the modules form a closed-loop system through a data flow and a feedback mechanism, dynamic association and automatic matching of multi-subject sub-link tax payment obligations and cash flow paths are achieved, and the tax auditing efficiency is improved.

The application relates to a multi-blockchain-based trusted hierarchical V2X data processing system, which comprises a vehicle layer, an RSU layer, a service layer and a cloud layer. The system proposes to divide the RSU network based on the RSU topological structure to reduce the data storage pressure; the system proposes a blockchain oracle mechanism in the Internet of Vehicles scene, through vehicle verification, node verification and cloud verification, all members in the system are organically involved in the data security protection process of the system, and the data security is ensured; the system proposes to use a particle swarm algorithm to optimize various parameters of the oracle, the optimization process is more scientific, and the effect is better than that of the experience-determined parameters.

A computing device is provided, including a processor configured to transmit, to a quantum coprocessor, instructions to encode a Markov decision process (MDP) model as a quantum oracle. The processor may be further configured to train a reinforcement learning model at least in part by transmitting a plurality of superposition queries to the quantum oracle encoded at the quantum coprocessor. Training the reinforcement learning model may further include receiving, from the quantum coprocessor, one or more measurement results in response to the plurality of superposition queries. Training the reinforcement learning model may further include updating a policy function of the reinforcement learning model based at least in part on the one or more measurement results.

The application relates to the technical field of blockchains, and provides a pension guarantee data auditing method and device based on a blockchain, equipment and a medium, which are applied to a blockchain system; the method comprises the following steps: receiving historical pension guarantee data sent by each access node based on an auditing equipment node, and downloading the historical pension guarantee data to the auditing equipment; receiving an evaluation score sent by the auditing equipment in a manner of an oracle; the evaluation score is obtained based on an organization portrait and a predefined algorithm by extracting behavior characteristic data from the historical pension guarantee data and then establishing the organization portrait; every preset period, it is judged whether the evaluation score meets preset requirements; if yes, an auditing process is started, so that the auditing equipment audits the historical pension guarantee data based on geographic information according to predefined criteria; in this way, the extensible oracle technology is used to reduce human intervention, data transmission is carried out based on the blockchain, data tampering is prevented, the data is guaranteed to be real and reliable, and the accuracy of the auditing is improved.

The invention discloses an intelligent contract enhanced data aggregation method based on large-scale language model and block chain cooperation, and relates to a block chain technology, large-scale language model application and data aggregation. Comprising the following steps: step 1, constructing a universal collaborative framework C-LLM which adopts a four-layer architecture of a user contract layer, an oracle contract layer, an oracle network layer and an LLMs layer, and performing secure data circulation between a block chain and the LLMs by utilizing hierarchical interaction; and step 2, in combination with a Sension-BERT semantic similarity analysis and truth discovery method, defining a semantic enhanced data aggregation method, and processing inconsistency of LLM generated texts and malicious node attacks.

The invention relates to the technical field of information security, and discloses a multi-modal biological recognition access verification method and system and a storage medium, and the method comprises the steps: collecting multi-modal biological information through terminal equipment, and carrying out the quality evaluation of each type of modal information, and obtaining a corresponding quality score; based on the quality score, the terminal equipment determines a target oracle node type, constructs a differentiated verification request, sends the differentiated verification request to a corresponding oracle node, and forwards the differentiated verification request to a back-end service system; and the back-end service system constructs the feature matching result, the quality score and the routing information into a context feature vector, inputs the context feature vector into a fusion decision model to generate a final verification conclusion, and finally executes authorization operation according to the conclusion. According to the invention, the verification accuracy and the operation efficiency of the system in a complex environment are effectively improved through the fusion decision of the adaptive routing decision and the context awareness, and the safety and the traceability of the whole link are enhanced at the same time.

An embodiment includes identifying, from a training dataset for training a model, a first unlabeled datapoint to present for labelling according to a first query strategy. The embodiment also includes issuing a query requesting a label for the first unlabeled datapoint. The embodiment also includes receiving a labeled datapoint in response to the query, the labeled datapoint comprising the first unlabeled datapoint as labeled by an oracle. The embodiment also includes generating a causal network based on labeled datapoints from the training dataset. The embodiment also includes receiving an instruction to modify the causal network. The embodiment also includes replacing the first query strategy with a second query strategy based on the instruction to modify the causal network. The embodiment also includes identifying, from the training dataset, a second unlabeled datapoint to present for labelling according to the second query strategy.

A system for resolving prediction market outcomes using secure hardware and trust-based scorer selection. The system scores each resolver based on their track record of accuracy, governance participation, and integrity alignment rather than token holdings. Resolution computations execute inside a tamper-resistant hardware enclave that prevents manipulation by platform operators or external attackers. Upon resolution, the system produces a sealed Provenance Token containing six cryptographic fields that bind the decision to its inputs, scoring model, enclave identity, and a non-replayable counter value, enabling anyone to independently verify resolution integrity. Anomalous resolver submissions are detected and quarantined before consensus using dual machine-learning algorithms running inside the enclave. The system generates regulatory compliance reports within the secure hardware and delivers results through authenticated API endpoints. Settlement automatically distributes payouts to holders of winning outcome shares.

The invention provides a distributed new energy asset chaining method and system based on error control, and belongs to the field of block chain technology and asset digitization. According to the method, operation data under a chain are obtained, reported through a plurality of independent oracle machine nodes and aggregated on the chain to form a consensus state, and then the consensus state is verified according to error tolerance parameters. If the verification is passed, updating a corresponding real world asset token state; and if the verification is not passed, the token is placed in a function-limited risk state, and the chain interaction of the token is limited. According to the method, the data error is converted into a manageable state on a chain instead of a system exception, so that the problem that the availability of the system is reduced due to the data error in the prior art is solved, and the robustness of the system is improved.

The present invention discloses an off-chain data acquisition system based on an oracle cluster, which relates to the technical field of off-chain data acquisition, including a user contract, an oracle contract, a database and an oracle cluster; the user initiates a request through the user contract, and the oracle contract encapsulates the request parameters as a chain code event and sends it to the oracle cluster; the oracle cluster includes at least one centralized oracle node, which is responsible for monitoring the chain code event and obtaining the processing right of the event by seizing the event lock. The node that obtains the processing right obtains the data source parameter by parsing the chain code event, initiates a data request to the data source and parses the response result, and finally calls back the user contract through the oracle contract to write the data back to the chain; all nodes in the cluster share a database, and the database implements event locks based on data tables, and the nodes in the cluster collaborate through event locks; the present invention can improve the efficiency of data acquisition, reduce the complexity of design, and ensure the high availability of services.

The invention discloses a block chain data acquisition and real-time synchronization method and device and a medium, and relates to an on-chain and off-chain data synchronization method in a block chain. An existing oracle model cannot guarantee the real-time performance of data uplink and on-chain propagation, and the method aims at overcoming the defect. The method comprises the following steps: S1, grading and screening original data through the review module to complete collection; s2, encrypting the data signature by a signature encryption module; s3, the data uplink module carries out uplink on the encrypted data; s4, the access control module authorizes member access authority; and S5, the data segmentation module carries out segmentation, recombination and acquisition of uplink data. S1-S3 use a longitudinal routing mechanism to ensure the real-time performance of data from a data source to the block chain, and S4 and S5 use a transverse routing mechanism to ensure the real-time performance of data transmission between members. According to the method, the transverse and longitudinal message routing, the open type optimal oracle selection protocol and the multi-channel data segmentation protocol are combined, the real-time performance and safety of data acquisition and uplink are improved, and the data requirements of high timeliness and high reliability are met.

The invention relates to the technical field of data verification, in particular to a data comparison verification method and system based on a block chain and an oracle machine. According to the method, the second to-be-compared data generated at all the metering terminals included in the aggregation control unit in the last period is acquired in the block chain through the data uplink contract, and the security and credibility of the source of the second to-be-compared data are ensured. The first to-be-compared data is obtained through the oracle machine, so that credible access to the under-chain data from the block chain becomes possible, the source channel of the multi-source data is expanded, and the first to-be-compared data is ensured to be true and credible. The aggregation of the second to-be-compared data and the comparison of the first to-be-compared data and the aggregated second to-be-compared data are performed through the data comparison contract deployed in the block chain, so that the influence of human intervention is avoided, and the fairness and justice of data comparison are ensured. And finally, the verification result is uploaded to the block chain for recording, so that the transparency and non-tampering property of the verification process are ensured.