695 results about "Integrity check" patented technology

The invention discloses a medical image encryption and secure storage method and system based on a block chain, and the method comprises the steps: obtaining the original data of a medical image, segmenting the original data of the medical image into a plurality of segments through a fragmentation technology, carrying out the encryption of each segment through a symmetric encryption algorithm, generating an encrypted segment set, and storing the encrypted segment set in a database; determining an integrity check value of the encrypted fragment set; according to the encrypted fragment set, adopting a distributed storage protocol to distribute each fragment to a plurality of storage nodes, recording a storage position and an integrity check value of each fragment to a block chain account book, and generating a storage index containing a storage path and check information; and establishing an access control strategy through the block chain smart contract, and if the obtained requester identity identifier and the authority level conform to the access control strategy, generating a dynamic authorization token including an access range and time limitation. According to the method, the privacy of the patient is protected, and meanwhile, the safety and availability of medical data are improved.

The invention discloses an electric power product operation fault detection system based on big data, and relates to the field of electric power fault detection systems, and the system comprises a data collection module which collects the multi-parameter operation data of various electric power products, including electrical and equipment states and environmental parameters, can dynamically adjust the collection frequency, and caches and encrypts the transmission data; the data preprocessing module is used for carrying out abnormal value correction, noise removal, normalization and integrity check; the feature extraction module is used for extracting key and time-frequency domain features by using multiple algorithms, selecting sensitive features according to a fault mode and identifying newly added features; and the fault detection model construction module constructs a model by combining machine learning and deep learning algorithms with ensemble learning and the like, and can update training. Through multi-module cooperation, features are effectively extracted to construct the model, accurate fault diagnosis and prediction are realized, visual display and knowledge support are provided, the intelligent level and efficiency of power product fault detection are improved, and stable operation of a power system is guaranteed.

The invention relates to the technical field of block chains, in particular to a supply chain data security sharing method based on a block chain. The method comprises the following steps: firstly, defining user roles and corresponding permissions in a supply chain system to generate an access control list; and then, collecting historical behavior data, access records and current system states of the requesting users, and adjusting roles and permissions of the users in real time by using predefined rules and a machine learning model. And then, based on the hybrid access control strategy, matching an access request of a user, generating an access decision, then generating an access operation instruction, executing an operation of data decryption or data encryption maintenance, and after the operation is completed, carrying out integrity check and consistency verification. And finally, collecting all record data generated in the access control process to optimize an updating mechanism of the access control list and realize continuous improvement and optimization. According to the invention, through dynamic adjustment of the access authority, the flexibility and efficiency of access control of the supply chain system are improved.

The invention provides a water conservancy industry electronic dark bidding document enterprise internal examination method and system based on artificial intelligence, and belongs to the field of water conservancy industry bidding. Performing automatic pre-auditing on the bidding file: performing compliance inspection and integrity inspection, identifying problems existing in the bidding file, and providing improvement suggestions to ensure that the problems conform to the basic requirements of electronic dark label review; carrying out data standardization and cleaning on the bidding file: carrying out semantic extension and ambiguity elimination, identifying images, tables and handwritten contents in the bidding file, identifying a main body structure of the water conservancy design drawing, extracting engineering quantity list data, and carrying out compliance verification; identifying an abnormal behavior in the bidding file through a machine learning model; and an internal examination decision tree is constructed according to preset key indexes and score weights of the water conservancy project, an interpretable artificial intelligence algorithm is utilized to carry out internal examination decision making on the bidding document, an internal examination score result is fed back, and specific score deduction reasons are explained. And the standardization and the accuracy of internal examination of the bidding document are improved.

Systems and methods for securing agent communications in a multi-agent system including deploying an agent to communicate with external servers, instantiating a sidecar security service in communication with the agent and including at least one of a guardrails service, a security layer, an encryption module, and an integrity checker configured to validate resources tools using hash-based verification mechanisms. Communications including messages between the primary and the external servers are intercepted by the sidecar security service, which then performs at least one of filtering the one or more messages by the guardrails service, authenticating one or more server connections by the security layer, encrypting one or more outbound requests by the encryption module, or verifying an integrity of resources and tool definitions by the integrity checker.

The invention discloses a data integrity protection method in an archive record tracing process based on a block chain, and the method comprises the steps: generating a hash value for each archive record as a tracing starting point, carrying out the traversal from the tracing starting point, generating an integrity check code when passing through a node of the block chain every time, comparing the current time with an archive secrecy period, and carrying out the data integrity protection. The method comprises the steps of obtaining an access control result, creating an encryption index for an archive record allowed to be accessed by a user in the access control result, selectively exposing data and obtaining identification data through the encryption index based on a traceability purpose, decomposing a traceability request into a plurality of sub-requests, and distributing the sub-requests to different block chain nodes to perform traceability processing based on the identification data. And aggregating different sub-query results to obtain a final traceability result. According to the method, a highly safe, reliable and transparent data integrity protection mechanism is provided for archive recording by utilizing the core characteristics of the block chain, the data integrity is enhanced, and meanwhile, the method has relatively good interpretability.

The invention relates to an alliance chain-based energy data sharing method and device, and a medium, and the method comprises the steps: collecting and preprocessing energy data based on a TEE, encrypting the data in the TEE, uploading the data to an IPFS, generating a hash value, and binding a data owner identifier; when the verification request is responded, integrity verification, numerical value verification and other operations are executed, and an encryption result is generated and returned to the demand side. After verification is passed, copyright information is embedded according to a data type matching watermarking algorithm, the IPFS is re-encrypted and uploaded, and a shared hash value is obtained. And storing the hash value and the decryption key into the block chain through the consensus node of the alliance chain, and transmitting the hash value and the decryption key to the demand side. And after the demand side decrypts and obtains the data, extracting the watermark and comparing the watermark with the on-chain parameters for verification. According to the method, sharing and verification of the data in an encryption state are ensured, privacy protection and use controllability are considered, and the problems of data leakage, tampering and ownership tracing in traditional sharing are solved.

The invention discloses a communication method of vehicle-mounted TBOX equipment, which relates to the technical field of equipment communication and comprises the following steps of: initializing a communication module of the vehicle-mounted TBOX equipment; performing channel selection by using a communication module to obtain channel information; performing spectrum allocation according to the channel information to obtain spectrum information; performing data encryption transmission according to the frequency spectrum information to obtain encrypted data; performing integrity verification on the encrypted data to obtain complete data; performing network load prediction according to the complete data to obtain a prediction result; adjusting the bandwidth according to the prediction result to obtain bandwidth data; and performing data packet priority management according to the bandwidth data. According to the method, the prediction accuracy and the overall communication efficiency are improved, the data transmission sequence can be flexibly adjusted according to the real-time network environment, the transmission reliability of key data is improved, and the risk of important information loss or delay caused by sudden network congestion is reduced.

The invention discloses a business data quality treatment method supporting system hidden danger identification, and relates to the technical field of computer information processing, and the method comprises the steps: S1, collecting a real-time batch tracking data stream from an enterprise inventory system through a multi-source data interface, and obtaining an initial data set containing inconsistent formats and missing batch numbers; s2, scanning a data stream according to the initial data set by applying a preset automatic detection rule, judging positions and types of abnormal points by utilizing a rule matching mode and a threshold comparison mechanism to obtain an abnormal point set, and activating a real-time stream analyzer to process field complete verification to generate an abnormal log record; according to the business data quality treatment method supporting system hidden danger identification, real-time and accurate anomaly detection and repair are realized, the consistency and reliability of inventory data are improved, and the enterprise inventory management efficiency is remarkably optimized.

The invention relates to the technical field of electronic cigarette cartridge authentication, in particular to an electronic cigarette cartridge anti-counterfeiting authentication system based on an encryption technology, which comprises an authentication parameter capture module, a cigarette rod data transmission module, a contact connection verification module and a key activation control module. According to the invention, through the dynamic data extraction and grouping processing of the identification code and the encryption key, the security and uniqueness of the identification information are improved, the circulation risk of counterfeit products is avoided, the association value of the combination of the dynamic authentication identifier and the identification code is calculated and stored, the dynamic update and traceability of the authentication data are realized, and the reliability and tamper resistance of parameters are enhanced; the unibus protocol realizes efficient transmission and real-time comparison of dynamic data, improves the accuracy and rapidity of comparison, ensures the comprehensiveness of data integrity check, reduces authentication misjudgment, combines key decryption and activation value calculation, strengthens an anti-counterfeiting function, realizes full-link security protection, optimizes resource consumption and improves the security and real-time performance of the system.

The invention relates to an intelligent medical record generation and quality control method and system based on a large model, belongs to the technical field of medical information and artificial intelligence, and solves the problems of low writing efficiency and non-uniform quality of medical records in the prior art. Comprising the following steps: constructing a medical field knowledge enhancement large model which has the capabilities of intention recognition, medical record generation, term standardization check, format integrity check, information extraction and logic consistency check; when input information of a to-be-generated medical record is received, generating a complete medical record through intention recognition and medical record generation capability of the medical field knowledge enhancement large model and the constructed medical record template library and medical database; and when a medical record to be subjected to quality control is received, quality control suggestions are generated through the capabilities of term standardization check, format integrity check, information extraction and logic consistency check of the medical field knowledge enhancement large model and the constructed medical knowledge graph. And efficient generation and quality control of the medical record are realized.

The present invention provides an autonomous computing system for cryptographic asset tokenization, digital currency operations, redemption, detokenization, and full lifecycle management of tokenized assets. The system leverages formal cryptographic proofs, hybrid off-chain and on-chain ledger synchronization, and automated execution protocols to enhance regulatory compliance, asset-backed stability, and operational autonomy. Smart contracts, cryptographic hash-based commitments, and distributed validation mechanisms ensure secure, verifiable, and tamper-resistant transactions across decentralized, centralized, and hybrid environments. The system governs the entire token lifecycle by intrinsically linking asset state validation to both on-chain and off-chain records. Hardware-agnostic cryptographic processing enforces governance rules, validates asset-backed token states, and prevents over-issuance. Real-time integrity checks and automated reconciliation deliver a scalable, cryptographically secured framework for autonomous management of tokenized assets and digital currency transactions, minimizing reliance on intermediaries.

The present application provides an interface calling method, comprising: a controller receiving a natural language description inputted by a user, acquiring a first prompt template corresponding to a first sub-task among a plurality of sub-tasks, concatenating the first prompt template with the natural language description inputted by the user, and inputting the concatenated result into a language model, so as to obtain an inference result outputted by the language model according to a first answer template corresponding to the first sub-task; and when a parameter integrity check sub-task among the plurality of sub-tasks is being executed, and when an inference result of said sub-task indicates that necessary parameters of a target interface to be called are complete, the controller calling the interface on the basis of the necessary parameters of the target interface, and presenting an interface calling result to the user. By means of specific sub-task splitting, the method reduces the pressure on the language model when performing logical reasoning, and improves the accuracy of inference. In addition, according to the method, specific prompt and answer templates are designed for the sub-tasks, so that the model can perform inference according to the templates and output inference results, thereby reducing randomness and improving stability.

The embodiment of the invention relates to the technical field of information, and discloses an intelligent multi-source data quality evaluation and verification method and device, a medium and a product, and the method comprises the steps: converting intelligent multi-source data into standardized format data; performing quality evaluation on the standardized format data, wherein the quality evaluation comprises at least one of integrity check, availability check and consistency check; loading a robot URDF model corresponding to the standardized format data, driving the URDF model to move according to joint data, and synchronously playing corresponding visual data for realizing linkage playback of model actions and visual pictures; analyzing linkage playback through the first large model and / or the second large model; wherein the first large model is used for judging the physical safety of the robot action, and the second large model is used for judging the high-level semantic correctness of the robot action and task annotation, so that a high-quality and reliable self-service intelligent data set is constructed.

According to an embodiment, a method includes adjusting a reference generator into a first configuration based on a temporary trim value resulting, in a first reference voltage and a first reference current being generated for a first memory. The method further includes performing an integrity check on an initial set of data downloaded from the first memory based on the first reference voltage and the first reference current. The initial set of data includes a first trim value. The method further includes downloading contents from the first memory into a second memory in response to a successful integrity check after adjusting the reference generator into a second configuration. In the second configuration, the reference generator generates a second reference voltage and a second reference current for the first memory. The reference generator is adjusted by the first trim value in response to a successful integrity check.

The invention discloses a large file concurrent uploading method and system based on a dynamic fragmentation strategy and resource optimization, and the method comprises the steps: a client generates a file fingerprint according to the file size of a large file and metadata, and dynamically calculates the fragmentation size of the large file; the client carries out fragment cutting on the large file according to the calculated fragment size, establishes a concurrent uploading queue and uploads a plurality of fragments to a server side in parallel; the server selects an optimal storage node to store each fragment based on a consistent hash ring and a multi-dimensional weight model; the client side and the server side track a fragment uploading state through a fragment serial number and a cyclic redundancy check (CRC) value, and after all fragments are uploaded, integrity check and logic recombination are carried out; and when network interruption or uploading failure is detected, the client side and the server side execute an intelligent retry strategy or a splitting rescheduling strategy of breakpoint resume and failure fragmentation.

The invention relates to a video access method and device, a video storage method and device, computer equipment, a storage medium and a computer program product. The embodiment of the invention can be applied to various scenes such as cloud technology, artificial intelligence, intelligent traffic, auxiliary driving and the like. The method comprises the steps of receiving a video access request; comparing an access video identifier in the video access request with a video identifier in each piece of image metadata on the block chain to obtain target image metadata, and extracting a target frame identifier from the target image metadata; comparing the target frame identifier with a frame identifier in each piece of storage metadata on the block chain to obtain target storage metadata; acquiring a distributed storage position corresponding to the target storage metadata, and extracting a target video frame based on the distributed storage position; performing integrity verification on the target video frame by using the integrity verification parameter; and under the condition that the integrity verification is passed, constructing a return video corresponding to the video access request based on the target video frame.

The invention discloses an education courseware generation method based on deep learning. The method comprises the following steps: S1, generating a standardized teaching document set; s2, obtaining a teaching element set; s3, outputting a slide sequence first draft, a sparse expert activation strategy first draft and a format parameter vector first draft; s4, obtaining an optimized sparse expert activation strategy, an optimized format parameter vector and an optimized slide sequence; s5, obtaining a structured PPT draft; s6, performing teaching structure integrity verification and visual hierarchy consistency verification on the structured PPT draft, if the verification is not passed, converting a verification result into a fitness penalty signal, feeding back the fitness penalty signal to the pigeon flock optimization algorithm, and returning to the step S4; and if the verification is passed, outputting a structured PPT final draft. The method ensures that the finally output structured PPT has uniformity and teaching performance in expression logic, page layout and visual style, and the manual adjustment workload of teachers is greatly reduced.

The Somatic Artificial Intelligence Data Systems (SAIDS) invention provides a method, system and apparatus for user-controlled data curation, privacy, and monetization. Leveraging a Generative Artificial Intelligence Agent (GAIA), SAIDS enables the collection and real-time processing of multimodal data, including biometric and environmental inputs, through wearable or standalone devices. GAIA anonymizes data, detects unauthorized use via integrity checks, and supports user decisions to either opt-in for economic benefits through data sharing or opt-out for enhanced privacy. This system democratizes data ownership by empowering users to retain control and derive value from their personal data in a privacy-preserving manner.

The embodiment of the invention discloses a multi-level safety protection system and method based on an electric power internet of things operating system. The system comprises a security module, a firmware integrity verification module, a kernel protection module and a file encryption module. The security module is used for performing security protection on security startup, isolation, intelligence and network in the electric power internet of things operation system; the firmware integrity verification module is used for performing integrity check on firmware of the electric power Internet of Things operating system and protecting a kernel, a memory, process management and files of the electric power Internet of Things operating system at the same time; and thus, protection in the starting and running processes of the electric power internet-of-things operation system is facilitated. The security protection system is established on the underlying security of the electric power Internet of Things operating system, is beneficial to the construction of an omnibearing protection mechanism of the electric power Internet of Things operating system, and prevents the electric power Internet of Things operating system from being attacked and data from being stolen.

The invention discloses a homomorphic encryption-based cross-industry health insurance data sharing and privacy protection method, and relates to the technical field of health insurance data security, and the method specifically comprises the steps: standardizing medical and insurance industry core data, quantifying key indexes such as a disease clinical risk value and an occupational basic risk coefficient, achieving the format unification of cross-industry data, and achieving the privacy protection of the cross-industry data; further generating ownership, risk and business labels, carrying out encryption processing on data through homomorphic encryption on the risk labels based on three scenes of data sensitivity and business influence grading, business label binding pricing, underwriting and claim settlement prediction, adding an integrity check code to high-risk data, screening ciphertexts based on the labels, and then executing fusion calculation; the comprehensive risk adjustment coefficient ciphertext is generated, the data integrity is verified, the comprehensive risk adjustment coefficient is obtained after collaborative decryption, the comprehensive risk adjustment coefficient is applied to premium pricing, underwriting conclusion generation and claim risk pre-judgment, and the scientificity and accuracy of health insurance pricing and underwriting decision making are improved.

Systems and methods leverage a multi-stage artificial-intelligence pipeline to convert raw point-of-sale data into bank-grade digital receipts. A convolutional-OCR front end extracts line-item text, which a bidirectional-LSTM classifier normalises and categorises in real time, learning continuously from user feedback. A graph-based anomaly detector flags suspicious spend patterns, while a recommender sub-engine delivers personalised rewards and sustainability insights by fusing purchase context with external carbon-intensity data. The enriched receipt is cryptographically hashed, streamed through an encrypted gateway, and auto-matched to the corresponding payment entry inside the banking core. By driving extraction, classification, enrichment and integrity checks entirely through AI, the system eliminates manual mapping and enables immediate, tamper-evident reconciliation across heterogeneous merchants and payment rails.

The invention provides an LLM-based multi-cloud storage intention decomposition optimization method, system and device, and belongs to the technical field of network communication and cloud computing. The method comprises the following steps: receiving fuzzy multi-cloud storage intention input of a user; performing semantic analysis on the user input, and extracting a parameter key value pair matched with the strategy tree model; carrying out information validity check on the extracted parameter key value pairs; the strategy tree model is filled with effective information, parameter integrity check is carried out, and if the information is incomplete, strategy tree parameters are supplemented through multiple rounds of dialogues; whether the filled strategy tree parameters need to be modified or not is confirmed to a user through the vertical LLM, if the user needs to modify the filled strategy tree parameters, parameter information is updated, and if the user confirms the information, follow-up operation is carried out; and generating an executable storage strategy according to the strategy tree model confirmed by the user. According to the method, the operation complexity of a user in a multi-cloud storage scene is reduced, and the accuracy, flexibility and reliability of storage strategy generation are improved.

The present invention is a system and method to help with resolving the pervasive issue of unauthorized external service accounts and subscriptions created by employees within an organization. The present invention seeks to provide users with a system that strategically analyzes organizational email communications, which serve as a rich data source for identifying unauthorized external accounts and services. The system accesses each email account under an organizational domain, wherein each email is cleared of unnecessary content. Additionally, an LLM analysis performs various cross checks, and an AI integrity check verifies all LLM responses. Finally, the system and method documents and report all findings to the organization.

An integrated circuit (IC), including multiple functional units for performing operations of the integrated circuit, provides security of a clock configuration at least during security operations. The IC includes a clock management subsystem for providing one or more clock signals to the functional units. The clock management subsystem is reconfigurable to adjust characteristics of the clock signal(s) or to select from among multiple clock sources from which the clock management subsystem generates the clock signal(s). The IC also includes a security subsystem for performing security operations within the IC and coupled to the clock management system to prevent alteration of a configuration of the clock management subsystem while the security operations are performed. The clock management subsystem performs a clock integrity check in response to the security operations before the security operations are performed. The security operations are not performed if the clock integrity check fails.

The invention discloses a multi-model intelligent management scheduling method and system. The method comprises the following steps: receiving a to-be-registered model and corresponding metadata, and executing integrity check to generate an integrity check result; generating a model identifier for the to-be-registered model according to an integrity check result, and storing the model identifier into a model storage warehouse; receiving a deployment request, and extracting a target model file and target metadata according to the deployment request; selecting a target computing node according to the target metadata; configuring a running environment according to a deployment environment requirement, and combining the target model file with the running environment to obtain a container mirror image; creating a containerized operation instance based on the container mirror image, and configuring a network access endpoint; predicting the page view of the network access endpoint to obtain predicted page view data; and adjusting the number of the containerized operation instances according to the predicted page view data and the system resource use data. By implementing the technical scheme, the problems of hysteresis and lack of perspectiveness of resource adjustment based on a real-time system load are solved.

A user equipment receives a first message for initial Access Stratum (AS) security activation via a higher layer protocol, wherein the first message includes configuration information for security in a lower layer protocol and the first message is included in a second message of the lower layer protocol. In response to receiving the first message, the UE derives an integrity key for the lower layer protocol based on the configuration information, and it performs an integrity check on the second message based on the derived integrity key.

The invention is suitable for the technical field of information security, and provides an Android APP multi-tamper-proofing method, which comprises the following steps: acquiring a dex file of an APP, and encrypting the dex file by adopting a reinforcement algorithm to generate a dex reinforced file; a signature obfuscation algorithm is adopted, obfuscation code segments are embedded in the dex reinforcement file, and a signature verification module is generated; carrying out encryption processing on the resource file of the APP by adopting an encryption storage algorithm to generate a resource encryption file; when the APP is started, secondary integrity detection is carried out on the APP based on the signature verification module; if the integrity of the APP is not destroyed, loading the resource encryption file, and carrying out decryption operation on the resource encryption file; and after the decryption operation, the key business logic code segment is verified in the APP operation process through the operation verification method, the tampering and attack resisting capability of the APP is effectively improved, and therefore the safety and integrity of the APP are protected.

The invention provides a data compliance migration method which comprises the following steps: acquiring data protection regulation change information through a regulation monitoring module, extracting key terms and geographic position parameters, and generating a compliance parameter set; triggering data classification identification according to the regulation change information, analyzing content features and sensitive levels of stored data, and determining risk classification of data blocks; distributing the data blocks to different transmission queues according to the risk classification, and generating a data migration task list; dynamically scheduling a data migration time window and a transmission quantity according to the risk classification and the optimal migration path; starting a parallel data transmission process, and executing a data migration operation; carrying out integrity check on the transmission data through a check algorithm, and confirming a transmission state; and the monitoring module is used for detecting service response time in the migration process and adjusting the migration progress and the switching opportunity.

The present application relates to messaging between instances of a microservice in a decentralized architecture. A computer device hosting an instance may include a memory storing instructions to operate a microservice and a processor. The instance receives a message for the microservice from another instance of the microservice, the message including a branch of a hash tree with at least a block for a root hash of a central node, one or more blocks for intermediate nodes, and a leaf block including message content. The instance places at least the leaf block into a local hash tree based on the branch of the hash tree. The instance verifies an integrity and an order of the message based on the root hash and the location of the leaf block in the local hash tree. The instance acts on the message content in response to verifying the integrity and the order.