886 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.

[Problem]When AMF changes from one AMF to another AMF, there is a problematic situation or an unclear situation for communication procedure between nodes including the AMF related to the communication procedure.[Solution]A communication apparatus includes means for receiving a message. The message includes information related to an access type. The communication apparatus includes means for using a Non Access Stratum (NAS) security context to perform an integrity check related to a registration request message. The NAS security context corresponds to the information related to the access type.

The invention relates to the technical field of data synchronization, and discloses a distributed account book remote data synchronization method and system, and the method comprises the steps: carrying out the Hash mapping calculation of all nodes of a distributed account book system, and obtaining a distributed storage architecture; performing hierarchical network construction on the nodes, and setting an inter-region remote synchronization link and an intra-region local synchronization link to obtain a double-layer communication architecture; performing parallel compression coding, digital signature generation, transmission scheduling arrangement and consistency verification processing on the data blocks to obtain a node synchronous data set; calculating a correlation coefficient of node processing delay and network transmission delay to obtain a synchronous delay analysis model; based on a data block corresponding to the synchronous delay analysis model, adding a time sequence identifier and calculating an integrity check code, and generating a synchronous reliability guarantee mechanism; according to the method, the consistency and the traceability of the distributed account book data are ensured.

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.

Provided in the present application is a communication method, the method comprising: a network device determining a security algorithm, wherein the security algorithm comprises a portion for performing confidentiality protection and a portion for performing integrity protection; the network device activating a security protection between the network device itself and a terminal device on the basis of the security algorithm and a security key, wherein the security key is a key shared between the terminal device and the network device; and the network device receiving a securely protected uplink message from the terminal device, using the security key as an input key of the portion for performing integrity protection in the security algorithm to perform integrity verification on the uplink message, and using the security key as an input key of the portion for performing confidentiality protection in the security algorithm to decrypt the uplink message. The security algorithm can implement both confidentiality protection and integrity protection, and a network device can perform an integrity check and decryption on the basis of the same security key, thereby avoiding potential security vulnerabilities existing in a combination of a confidentiality security protection algorithm and an integrity security protection algorithm.

A secure processing system configured to produce a hash based digital signature of a message, including: random number generator (RNG); a monotonic counter device configured to produce a monotonically increasing counter value; a hash accelerator configured to produce a hash of the message based upon a random number from the RNG and the counter value; and a run time integrity check (RTIC) device configured to check the integrity of the operation of the hash accelerator based upon the counter value.

The invention discloses a WAPI, CCMP and GCMP encryption and decryption coexisting parallel processing system and method for a wireless local area network. The system comprises a transmitter and a receiver. The transmitter is used for reading a plaintext data frame to be encrypted from an application layer, and the plaintext data frame to be encrypted comprises a first MAC frame header, a first security header and a first frame body; reading plaintext data from the first frame body to enable the MAC layer to carry out encryption processing through an encryption module, send encrypted information to a physical layer and then transmit the encrypted information through an air interface; the receiver is used for receiving a to-be-decrypted ciphertext data frame from the air interface, and the to-be-decrypted ciphertext data frame comprises a second MAC frame header, a second security header and a second frame body; reading the ciphertext data and the integrity check MIC ciphertext value from the second frame body, so that the MAC layer sends decryption information to the application layer after carrying out decryption processing through a decryption module; the encryption module encrypts plaintext data; and the decryption module decrypts the ciphertext data. Therefore, the hardware circuit scale is remarkably reduced, and the space occupancy rate is remarkably 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 discloses a medical information management system based on a block chain technology. The medical information management system comprises a data acquisition module, an identity authentication module, a medical data storage module, a data sharing module, an intelligent contract module and a patient privacy protection module. The invention belongs to the technical field of medical information, and particularly relates to a medical information management system based on a block chain technology. According to the scheme, a security parameter, a public key and a random number are generated to initialize a process, a registration center carries out private key matching to complete server registration, and a device password is calculated according to a device ID; splicing the device password and the security parameter in the registration center and carrying out hash processing on the device password and the security parameter; the method comprises the following steps: initializing medical data, partitioning the data, calculating a verification identifier and a file identifier, and performing information integrity check; patient sensitive information ranges and objects to be encrypted are determined, encryption algorithms and key lengths are selected according to types and importance degrees, access levels are distributed, different keys correspond to different access levels, and fine management is achieved.

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.