1048 results about "Chain network" patented technology

The invention relates to the technical field of server upgrading, and discloses a server firmware remote upgrading method and system, and the method comprises the steps: a management node obtains a device identifier list and target firmware version information of a to-be-upgraded server, and uses a distributed task scheduling algorithm to divide tasks; transmitting an upgrading instruction and a data packet through an encryption channel, and generating an incremental packet by using a differential upgrading technology; data transmission is guaranteed through heartbeat detection and breakpoint continuous transmission; after pre-verification of the server-side security sandbox, upgrading and isolating tasks in an idle period; verifying by adopting a gray release strategy, and automatically rolling back if the verification fails; and storing an upgrade state and a log by means of a block chain network. The system comprises corresponding function modules. According to the method, the upgrading efficiency, safety and reliability are improved, the influence on services is reduced, data cannot be tampered and can be traced, the problems existing in a traditional upgrading mode are effectively solved, and the method is suitable for various server firmware remote upgrading scenes.

A system may include an Al convergence system of systems for a value chain network environment.

The invention discloses a trusted data space cross-domain collaborative analysis method based on privacy computing, which comprises the following steps: step 1, trusted data space construction: edge computing nodes are deployed in a plurality of data owners participating in cross-domain collaborative analysis, and each edge computing node is interconnected through a block chain network to form a distributed trusted data space; a strategy engine is configured in the trusted data space, and the strategy engine is used for defining a data use permission, a privacy protection level and a calculation task life cycle management rule; and step 2, dynamically selecting privacy computing protocols, and selecting at least one privacy computing protocol from a pre-configured protocol library according to the data type, privacy protection requirement and computing complexity of the collaborative analysis task. When the scheme is implemented, the data participates in calculation in a ciphertext or desensitization form in the whole process, and the original data is not out of the domain, so that the privacy compliance requirement is met; and data use rules are automatically executed through block chain evidence storage and the intelligent contract, so that malicious node tampering is prevented.

The invention discloses a digital asset secure transaction system and method based on a block chain, and belongs to the cross field of block chain technology and financial science and technology. The system adopts a layered architecture design and comprises an intelligent contract execution layer, a distributed account book storage layer and a cross-chain interaction layer. The transaction method comprises the following steps: generating a digital identity certificate based on asymmetric encryption, and realizing privacy protection through zero-knowledge proof; a secure transaction channel is constructed by adopting a multi-signature mechanism, and sensitive data processing is performed in combination with a trusted execution environment; and designing a dynamic fragmentation strategy to optimize the transaction throughput, and establishing an on-chain and off-chain collaborative verification mechanism. The innovation point is that a double-layer verification model combining a verifiable delay function and a threshold signature is provided, and millisecond-level confirmation is realized while the transaction irreversibility is ensured. The system supports multi-chain asset atomic exchange, and interoperability of different block chain networks is realized through a heterogeneous cross-chain gateway. The scheme has the characteristics of high transaction confirmation speed, high privacy protection level and high system expansibility.

The invention relates to the technical field of data processing, and discloses an AI knowledge base construction method and system for intelligent water conservancy. The method comprises the following steps: forming a water conservancy intelligent perception data set by integrating hydrological monitoring data, engineering operation records and expert literatures; knowledge sprouts are identified, and a water conservancy native knowledge unit is generated; key features are extracted, knowledge element decomposition is carried out, and a knowledge evolution chain network is constructed through correlation analysis; screening in combination with a historical application effect and expert evaluation to obtain a preferred knowledge body; performing intelligent reconstruction on a scheduling rule, risk prevention experience and an operation and maintenance method to form an innovative knowledge base; and finally, intelligently matching with real-time engineering requirements to generate an intelligent water conservancy AI knowledge base. According to the application, by establishing a self-adaptive knowledge acquisition, organization and application mechanism, the knowledge base can autonomously update the knowledge content according to the environment change, the knowledge structure is optimized, and the intelligent operation management level of the water conservancy project is improved.

The invention provides a big data mining method and system applied to supply chain financial businesses, and the method comprises the steps: firstly obtaining real-time heterogeneous data streams of a plurality of participants of a target supply chain network, covering structured orders, unstructured logistics texts and semi-structured settlement document data, carrying out the multi-modal feature fusion, and carrying out the real-time heterogeneous data streams, including the structured orders, the unstructured logistics texts and the semi-structured settlement document data, of a plurality of participants of the target supply chain network; the method comprises the following steps: generating a supply chain feature matrix containing static and dynamic features of entity nodes, constructing a supply chain time sequence diagram network based on the supply chain feature matrix, representing participants by nodes, representing transaction events with timestamps and transaction strength weights by edges, hierarchically aggregating features by using a pre-trained time sequence diagram convolutional network, extracting global transaction modes and local abnormal fluctuation features, and constructing a supply chain network; and finally, generating a supply chain risk conduction topological graph which comprises a risk propagation path and an intensity parameter, and triggering a real-time risk early warning signal so as to realize accurate insight and timely early warning of the supply chain financial risk.

The invention relates to the technical field of transaction processing systems, and particularly discloses a trusted monitoring auditing system fusing TEE and a block chain, which comprises the following steps: generating a transaction instantaneous state abstract containing a key information field at a key node of a business process through a trusted execution environment, signing, anchoring a hash value of the transaction instantaneous state abstract to a block chain network, and storing the signature abstract under the chain; and during auditing, by comparing integrity verification of on-chain hash and under-chain abstract and TEE signature verification, dual authentication of transaction authenticity and environment reliability is realized. Through the collaborative architecture of the TEE and the block chain, the transaction core data state and the credible environment proof are deeply fused, so that the audit verification can be independently completed without depending on a centralized database, the problem that post-event tracing depends on the credibility of the log in the traditional audit is fundamentally avoided, and the audit verification efficiency is improved. And a lightweight credible verification basis is provided for a cross-mechanism cooperation scene.

A value chain network control tower system comprises a processor and memory configured to execute a know your model system that manages the complete lifecycle of Al models in enterprise environments. The know your model system performs model intake and registration actions including model documentation collection, registration procedures, metadata collection, input / output interface standardization, legal and licensing validation checks, and security validation. The system conducts comprehensive model evaluation and risk assessment actions by analyzing foundational properties, task performance, safety and risk management, alignment and compliance characteristics, operational metrics, and tooling transparency capabilities. The know your model system executes model deployment actions through automated environment validation, predeployment approval processes, and controlled production deployment with continuous monitoring.

The invention relates to the technical field of dispatching and emergency response, in particular to a supply chain multi-node real-time collaborative dispatching and emergency response system and method, and the system comprises a distributed data collection module which is used for obtaining the inventory data, logistics state and equipment operation parameters of each node in real time; the digital twin modeling engine is used for constructing a dynamic virtual mapping model of the supply chain network; the collaborative decision center generates a multi-objective optimization scheduling scheme based on a reinforcement learning algorithm; the emergency response trigger is used for automatically starting a graded emergency plan through abnormal mode recognition; according to the method, second-level response is realized through millisecond-level data synchronization and edge calculation, so that decision timeliness is improved, cross-node cooperation efficiency is improved by adopting multi-agent game and federated learning, and the punctuality rate of orders and the toughness index of the network are improved through multi-target Pareto optimization on the premise of controllable cost.

The invention provides a block chain-based clinical test data integrity system, and relates to the technical field of data processing, and the system comprises the following components: a multi-source heterogeneous data acquisition and preprocessing module, a multi-level encryption and under-chain data storage module, an alliance block chain network, and an alliance block chain network maintenance and verification shared distributed account book. The distributed account book only stores all digitally signed clinical test data fingerprints, metadata and operation logs, does not store original data, and is linked with the intelligent contract automatic management module, so that the clinical test data cannot be tampered in the whole life cycle from the source to archiving. Hash anchoring, digital signature and decentralized verification mechanisms of the block chain technically eradicate the possibility of unauthorized tampering of data, and ensure scientificity and reliability of clinical test results.

The invention discloses a supply chain resource optimization method and system based on atlas analysis, and the method comprises the following steps: constructing a supply chain atlas, and updating the supply chain atlas based on real-time supply chain data; key paths and low-efficiency paths in the supply chain atlas are identified through an atlas analysis algorithm, and bottleneck nodes are confirmed; generating an initial optimization strategy set based on the critical path and the bottleneck node; receiving a user interaction signal, determining an optimization operation type according to the user interaction signal, and dynamically correcting the initial optimization strategy set based on the optimization operation type; and executing the dynamically corrected initial optimization strategy set, and feeding back and updating the supply chain atlas based on an execution result. The method has the following advantages and effects: dynamic global analysis and real-time response of the supply chain network are realized, the resource allocation efficiency is improved in a complex supply chain environment, and the logistics interruption risk is reduced.

An information technology system for a distributed manufacturing network includes an additive manufacturing management platform configured to manage process and production workflows for a set of distributed manufacturing network entities through design, modeling, printing, and supply chain stages. The information technology system includes an artificial intelligence system configured to learn on a training set of outcomes, parameters, and data collected from the set of distributed manufacturing network entities of the distributed manufacturing network to optimize digital production processes and workflows. The information technology system includes a distributed ledger system integrated with a digital thread configured to provide unified views of workflow and transaction information to entities in the distributed manufacturing network.

The invention relates to a network security protection method and system based on a block chain, and aims to solve a series of challenges of identity authentication single-point failure, insufficient static block chain fragmentation, threat detection limitation, encryption algorithm security problem and the like in the existing network security protection technology. According to the method, an on-chain digital identity is generated by fusing an equipment unique identifier and user biological characteristics, dynamic authority management is performed based on the identity, network traffic is detected in real time by using a deep learning model of adversarial training, a threat detection result is generated, an authority level is updated according to the detection result through an intelligent contract, and meanwhile, the user experience is improved. A fragmented block chain network technology is adopted, the number of sub-chains is dynamically adjusted according to a network load, cross-chain threat intelligence synchronization is realized through a relay chain, in addition, a threshold signature and zero-knowledge proof technology is also adopted, permission change records and cross-chain data are encrypted and verified, the security and privacy of the data are ensured, and the security and privacy of the data are improved. According to the invention, the efficiency and reliability of network security protection can be effectively improved, and a safer and more reliable network environment is provided for users.

The invention discloses an intelligent city management information visualization comprehensive management method and system, particularly relates to the technical field of city management, and is used for solving the problem of misalignment of emergency response caused by false association and causal confusion in the prior art. Precise management is realized through multi-modal time sequence data feature alignment, causal chain network dynamic construction and a visual decision mapping technology, firstly, multi-dimensional event features of video monitoring, sensors and text work orders are extracted, a cross-modal association chain is constructed, interference chains are screened out through causal strength evaluation and anti-fact verification, and a visual decision mapping algorithm is established. According to the method, dynamic correction parameters are generated in combination with space-time weights and feedback priorities, finally, a visual guidance scheme is output by fusing a causal chain network and a geographic information system, decision optimization is driven through causal logic, and city event disposal accuracy and cross-department cooperation efficiency are remarkably improved.

A robot fleet management platform includes a job configuration system that determines tasks to be performed by robots of a robot fleet based on a job request and a first fleet objective. A proxy service applies fleet configuration services to the tasks to produce a data structure. An intelligence layer activates intelligence services to produce a robot task and associated contextual information that facilitates robot selection and task ordering. A job workflow system generates a workflow defining a performance order of the tasks. A workflow simulation system simulates performance of the job request based on the workflow to recursively redefine the tasks, the data structure, or the workflow until the simulation result satisfies a second fleet objective. In response to the simulation result satisfying the set of fleet objectives, a plan generator generates a job execution plan based on the set of robot tasks, the data structure, and the workflow.

The invention provides an engineering supply chain risk conduction analysis system based on a graph neural network and a method thereof. The method comprises the following steps: acquiring supply chain operation data from multi-level supply chain nodes; constructing a graph structure model between supply chain nodes according to the operation data, and identifying and quantifying an association relationship between the nodes; simulating the risk event occurrence of the supply chain node on the graph structure model; based on a graph structure model, calculating the probability and influence value of risk propagation from an occurrence node to other nodes, and identifying a main risk propagation path; using a Motif anomaly detection module to detect an abnormal sub-graph mode appearing in a risk propagation process in the graph structure model; performing representation learning and association prediction on the graph structure model by using a self-supervised graph neural network, and mining potential hidden risk association; by constructing a multi-level supply chain association map and introducing risk disturbance simulation, the system can quantify the conduction rule of the risk in a supply chain network from a global perspective, and can automatically identify hidden high-risk links and key propagation paths.

The invention discloses a method for enabling building supply chain information tracing and management based on a block chain, and relates to the technical field of block chains, and the method comprises the following steps: S1, constructing an information chaining platform for building supply chain management, enabling each participant node of a supply chain to access a block chain network, storing the full life cycle data of the supply chain through employing a distributed account book technology, and storing the whole life cycle data of the supply chain; the full life cycle data comprises data of decision making, design, construction, acceptance and operation and maintenance stages. According to the method for tracing and managing the full-life-cycle information on the building supply chain, the data is stored by adopting a distributed account book technology, the integrity and non-tampering property of the data are ensured, the accuracy and efficiency of data tracing are improved, the consistency and reliability of the data are further ensured through a Hash algorithm and a consensus mechanism, and the data tracing efficiency is improved. A credible data basis is provided for each participant of the supply chain, and the supply chain flow rule is automatically executed by deploying the intelligent contract.

A dynamic vision system includes a variable focus liquid lens optical assembly. The dynamic vision system includes a variable lighting assembly. The dynamic vision system includes a control system configured to adjust one or more optical parameters and data collected from the variable focus liquid lens optical assembly in real time. The dynamic vision system includes a control system configured to adjust the variable lighting assembly. The dynamic vision system includes a processing system that dynamically learns on a training set of outcomes, parameters, and data collected from the variable focus liquid lens optical assembly to train a set of machine learning models to control the variable focus liquid lens optical assembly to optimize collection of data for processing by the set of machine learning models.

A VCN process may receive, by a value chain network digital twin, information associated with a value chain network. A VCN process may provide the information to a set of Artificial Intelligence (AI)-based learning models, wherein at least one member of the set of AI-based learning models is trained to classify at least one of: an operating state, a fault condition, an operating flow, or a behavior of the value chain network and at least one member of the set of AI-based learning models is trained to determine a task to be completed for the value chain network. A VCN process may provide at least one of an instruction for executing the task in the value chain network digital twin and a recommendation for executing the task in the value chain network digital twin.

The invention discloses a data compliance privacy protection method based on a block chain, and the method comprises the following steps: S1, building a block chain network, and uploading original data; s2, classifying original data, marking sensitive data and encrypting the sensitive data; s3, dynamically distributing authority, and adjusting authority rules in combination with an immune mechanism; s4, completing permission condition verification, and storing a verification result and a log to the block chain network; s5, optimizing an auditing strategy, generating an auditing task and allocating resources; s6, cooperatively completing the auditing task, generating a global verification result and recording the global verification result; s7, adjusting an authority verification and auditing process, and generating a compliance report; and S8, recording a complete permission verification and auditing process. According to the method, the block chain technology is combined with dynamic authority management, privacy multi-party calculation and multi-scale modeling, so that data privacy protection, compliance management and high efficiency, safety and transparency of cross-regional collaboration are realized.

According to the face data privacy protection method and device provided by the embodiment of the invention, a credible authority management mechanism is constructed through a distributed network and a smart contract, and a multi-dimensional feature extraction scheme fusing geometric features and texture features is innovatively designed. The system adopts data fragmentation and homomorphic encryption technologies to carry out security processing on feature vectors, and dispersedly stores encrypted data in a block chain network, so that decentralized management of the feature data is realized. According to the method, feature comparison and identity verification are carried out in a ciphertext domain, the whole process is traceable in combination with a timestamp and an operation record, the problems of data security and privacy protection in a traditional face recognition system are effectively solved, and a safe and credible technical solution is provided for the field of biological feature recognition.

The invention is suitable for the technical field of data asset management, and provides a data asset management system based on a block chain and big data analysis, and the system comprises a first terminal which carries out the storage of the ownership information of data assets through a block chain network, and generates a storage data package; generating an evaluation result based on a preset technical index analysis model; writing the hash value of the evaluation result into transaction data of the main chain of the block chain, and generating an evidence storage voucher matched with the block chain transaction; an interaction data sequence is packaged for identity signature, encryption and compression to generate a target code stream, and the target code stream is sent to the second terminal; the second terminal decrypts the encrypted data in the target code stream by using a private key, decompresses the data by using a compression algorithm matched with the first terminal, and restores the data into an interactive data sequence; verifying the access authority and the transaction condition of the evidence storage data packet; checking the anchoring state of the evidence storage voucher on the main chain of the block chain; and the data transaction is completed, the data asset state report is generated, and the data element marketization configuration efficiency is improved.

The invention belongs to the technical field of data management, and discloses a research and development data traceability and collaborative management system based on a block chain, and the system comprises a sensing layer which is used for collecting multi-source research and development data on various research and development tool chains through a multi-protocol collection agent, carrying out the structural packaging of the data to generate metadata, and embedding a data blood relationship tracking mark in the metadata; false data filtering is carried out on the metadata by deploying a trusted execution environment; the chain network layer is used for dividing the filtered metadata into data fragments and respectively storing the data fragments in a distributed storage platform; applying a Hash algorithm to each data fragment to generate a corresponding Hash value; taking the hash values corresponding to all the data fragments as leaf nodes, constructing a fragment hash tree, and further obtaining global root hash; the security of research and development data is ensured, and the cooperation efficiency is improved.

The invention discloses an inland river water transportation facility monitoring data secure transmission method based on a block chain technology, and the method comprises the following steps: selecting an optimal sensor for data collection according to the geographic position and operation environment of a facility through a dynamic sensor switching mechanism, and eliminating errors caused by equipment faults and environment interference, after the collected data is subjected to time-space aggregation processing and classified according to geographic areas and time windows, based on a block chain node selection algorithm, an optimal node is selected for data transmission, the data is encrypted by adopting a hierarchical encryption strategy, the encrypted data is stored in a block chain network, and the data is transmitted to the block chain network through a threshold-triggered smart contract. And monitoring the stored data in real time, and automatically adjusting a monitoring scheme or starting an emergency mechanism when the stored data exceed a preset threshold value. The invention aims to improve the security and integrity of monitoring data transmission.

The invention discloses a block chain fragment optimization method and system, and particularly relates to the technical field of block chains. The method comprises the steps of generating an initial fragmentation scheme by obtaining a global fragmentation topological structure of a target block chain network; based on an initial fragmentation scheme, analyzing cross-chain interaction frequency and internal node connectivity between fragments, calculating a cooperation coefficient of each fragment, and identifying a high-frequency interaction subchain to form a fragment collaborative optimization subset; then, sub-node grouping analysis is carried out on high-frequency interaction sub-chains in the optimization subset, and reconstruction candidate fragments are screened out by combining in-chain transaction confirmation time and resource consumption; carrying out load state evaluation on nodes for reconstructing the candidate fragments, and optimizing load distribution through node migration simulation and inter-chain communication prediction to form an optimal fragment migration scheme; the migration scheme is applied to the target fragment, the consensus protocol path is adjusted in real time, the optimization effect is evaluated based on interaction data, fragment resource allocation can be dynamically optimized, network delay is reduced, and the overall performance is improved.

The system develops a set of complete traceability management system based on the block chain technology according to the quality safety and traceability management requirements in the production, processing and circulation processes of traditional Chinese medicinal materials, guarantees the traceability of the whole process from planting to consumption, improves the transparency of a supply chain, guarantees the rights and interests of consumers, and provides precise data support for supervision departments. The system adopts a front and back end separation architecture, a back end is developed based on SpringBoot and interacts with a Fabric block chain network, tamper-proof and verifiable storage of traceability data is realized, and data storage, quality examination and authority management are automatically executed through an intelligent contract; the front end is developed based on a Vue.js framework, smooth user experience is provided, and consumers can inquire complete traceability information of the traditional Chinese medicinal materials by scanning codes. System functions cover full life cycle traceability, block chain evidence storage, intelligent contract management, authority hierarchical control and data visualization, a supervision mechanism is supported to utilize big data analysis to accurately supervise quality problems, and market supervision efficiency is improved. The system guarantees the data security and transparency through the block chain, optimizes the supply chain management, improves the brand value, and assists the digital and standardized development of the traditional Chinese medicinal material industry.

The invention discloses a cross-border e-commerce block chain payment credit chain system and a method thereof, and realizes data sharing, information real-time synchronization and credit information dynamic transmission of each participant in a transaction by constructing an alliance block chain network. The system comprises a credit management module, a risk control module, an intelligent contract payment module, a digital currency exchange module and a security collaboration module, and multi-dimensional credit assessment, dynamic risk prediction and automatic payment are realized by using cross-domain technologies such as federated learning, trusted execution environment and homomorphic encryption. Through fund freezing, real-time digital currency exchange, payment triggered by performance conditions and other mechanisms, the cross-border payment clearing period is remarkably shortened, the transaction cost is reduced, the payment safety and supervision transparency can be improved, and the problems that traditional cross-border payment is low in efficiency, high in cost, difficult in risk control and the like are effectively solved.

The invention discloses a file fragment encryption transmission method and device based on a B / S architecture, and belongs to the field of information security. The problem of systematic contradiction among file transmission efficiency, safety and reliability is solved. The method comprises the following steps: determining a fragmentation threshold value, and carrying out self-adaptive fragmentation processing on an original file; respectively performing RSA public key encryption and AES random key secondary encryption on each fragment file to generate a double-encrypted file; writing the SHA-3 hash value of each fragment file and the timestamp information into a block chain network to generate a non-tampering meta-file; a multiplexing transmission channel is established, a meta-file and an encrypted file set are downloaded at the same time, and each fragment adopts an independent transmission thread; verifying the consistency of the Hash value of the downloaded file and the blockchain evidence, and executing an exponential backoff retransmission strategy on the fragments which fail in verification; and performing streaming decryption recombination on the verified fragments to generate a temporary file with a digital watermark. The method is mainly used in data transmission field.

The invention relates to the field of machine learning, in particular to a model weight confirmation method and device based on a block chain and a model fingerprint, and the method comprises the steps: carrying out the abstract compression of a model weight of each layer of network of a model, and obtaining a model weight abstract; performing Hash encryption and recording on the model weight abstract generated each time by adopting a Merkle tree structure to obtain a model fingerprint record; and uploading the model fingerprint record to the block chain network so as to verify the model fingerprint record. According to the invention, encryption processing is carried out on the model weight through the Hash encryption algorithm with the secret key, the model fingerprint is constructed in combination with the Merkle tree to generate a unique model fingerprint, the model fingerprint is uploaded to the block chain, the model fingerprint is combined with the block chain technology, a safe storage environment is provided for the model fingerprint, and the storage efficiency of the model fingerprint is improved. And the credibility of model ownership authentication and content tracing is enhanced.

The invention discloses a data asset secure storage method based on a block chain technology, and the method comprises the following steps: data preprocessing and fragmentation storage: carrying out the preprocessing of to-be-stored original data assets, extracting metadata information, and generating a unique hash identifier; through multi-chain collaborative storage, dynamic hierarchical encryption and cross-chain redundant backup, the security of data assets is remarkably improved, fragment storage is combined with a heterogeneous block chain network, the data storage efficiency is improved, and single-point failure and centralized attack risks are avoided; the anti-cracking capability is enhanced through dynamic encryption and distributed key management; a cross-chain synchronization mechanism ensures high availability of data, so that the data can be efficiently circulated in different block chains; the operation and maintenance cost is reduced through automatic verification and recovery driven by the intelligent contract, the auditing tracking and life cycle management functions meet the compliance requirement, and the method is suitable for data storage scenes in the high-sensitivity fields of finance, medical treatment and the like.