3915 results about "Authorization" patented technology

The invention discloses a data security dynamic evaluation system and a protection method, belongs to the technical field of information security, and is used for solving the problem of terminal equipment access control and behavior risk dynamic collaborative protection. The method comprises the following steps: generating fingerprints through terminal equipment features, verifying authorization, inputting access feature slices into a time sequence model by authorized terminal equipment, generating a trust score based on cosine similarity of a behavior sequence and a prediction sequence, and constructing a Markov model to dynamically select an authentication mode according to the trust score; calculating a risk index by combining network and geographic information, and distributing the risk index to a real or virtual environment; and the unauthorized terminal equipment distributes the virtual environment after registration. Differentiated monitoring is carried out, a time sequence library is established in the virtual environment, and doubt scores are generated through sequence matching; the state deviation of the real environment is calculated through a hidden Markov model, and the risk score is generated by fusing the multi-dimensional features. And based on the result management authority, the suspicion terminal equipment isolates and shrinks the authority, the compliance terminal equipment authenticates and migrates, and the access is regulated and controlled according to the minimum privilege principle and the time window mechanism.

The invention discloses a data ownership verification and authorization control method based on zero knowledge proof. The method comprises the following steps: constructing a traceable Merk tree structure on a block chain or a distributed account book; a data owner calculates data fingerprints and packages the data fingerprints into declaration nodes to be inserted into the traceable Merk tree; storing the ownership zero knowledge proof and the traceable Merk tree root hash into a block chain together; the verification party executes the zero-knowledge verifier contract on the chain to complete ownership verification without reading original data or identity plaintext; access control is realized after on-chain verification of the service party; triggering local heavy hash to update the traceable Merk tree root hash, and broadcasting a revocation event on a chain; and confirming legality of evolution and authorization change of all nodes. According to the method, the historical traceability and structural consistency of the data ownership and authorization relationship are ensured, and efficient traceability and anomaly detection of the node evolution chain are also realized.

Systems and methods disclosed herein automatically authorize, audit, and manage usage of protected digital content via agentic artificial intelligence (AI) models. A data access / usage request is received (e.g., from a graphical user interface) that is associated with digital assets licensed from third parties. The system uses a first AI agent set to identify the digital content and retrieve corresponding access policies from a distributed database. The system uses a second AI agent set (same as or different from the first AI agent set) to evaluate the request against the retrieved policy to generate a permission set and / or settlement instructions. The system uses a third AI agent set (same as or different from the first and / or second AI agent sets) to embed digital watermarks and / or cryptographic signatures into the accessed content, and to record an audit trail of access, authorization, and / or settlement events in a distributed ledger or database.

The invention discloses an urban multi-mode digital twin data asset security management method, and relates to the technical field of urban digital twin and data security, and the method comprises the steps: firstly building a unified access gateway, converging multi-department and multi-type data, and generating sensitivity annotation and privacy level metadata; performing differential privacy or desensitization and dynamically calibrating parameters at the local part of the data provider according to the labels; bookkeeping access, authorization and training on a permission alliance chain, and performing fine-grained permission control; through on-chain authorization, each node only uploads disturbed and encrypted model update, and a global model is obtained after secure aggregation; the governance layer continuously monitors logs, budget and model indexes and triggers strategy closed-loop regulation and control; and multi-agent reinforcement learning of a privacy agent and a performance agent is further introduced, a unified multi-target optimizer is formed through distillation, privacy, federation and permission strategies are refreshed online, and collaborative analysis and compliance sharing operation without data out of a domain are realized.

Techniques include optimizing a base access control policy, resulting in a residual access control policy, which is then indexed. Upon receiving an access request, the system retrieves the residual access control policy from the index using the request's attributes. The access request is then evaluated against the residual policy to make an authorization decision, which is promptly returned. This streamlined process efficiently evaluates and determines authorization, enhancing the speed and accuracy of access control decisions.

Systems and methods are provided for managing AI (Artificial Intelligence) agents interactions with electronic communications that are displayed at an electronic communications interface, such as an email interface. The systems parse electronic communications to determine whether they correspond to new or existing requests and actions to be performed when responding to the request(s). The systems also generate notifications identifying the set of actions with visual identifiers that visually distinguish the set of actions based on whether they have been completed or not and whether they need authorization to be completed. The systems also display selectable controls for controlling how the AI agent performs the actions.

The embodiment of the invention provides a dynamic knowledge graph-driven cross-department government affair data collaboration method and a dynamic knowledge graph-driven cross-department government affair data collaboration system. The method is applied to the technical field of computer science and technology, and comprises the steps of obtaining cross-department government affair service data and corresponding policy rule data, constructing a data knowledge graph and a policy knowledge graph, performing incremental updating and consistency verification on the knowledge graphs based on preset event information, and extracting a newest service state and a newest policy rule. A minimum necessary data view and an authorization range are generated through joint reasoning, efficient and safe collaboration of cross-department government affair data is achieved on the basis, and accurate authorization and compliance management of data access are achieved. According to the scheme, only necessary data is provided and the access permission is strictly controlled in cross-department government affair data collaboration, so that the data sharing efficiency, security and compliance are remarkably improved, and meanwhile, the risks of unauthorized access and redundant data transmission are reduced.

The invention discloses a government affair data dynamic authorization management method based on secure multi-party computing, and relates to the field of government affair data security authorization management, and the method comprises the steps: distributing a unique identity identifier for each participant, generating an asymmetric key pair through employing a national secret SM2 algorithm, registering a public key and mechanism attribute information to an alliance chain smart contract, and generating an identity certificate package; and based on attribute information in the identity credential packet, the participants cooperatively generate anti-quantum dynamic attribute-based encryption key fragments through a secure multi-party computing protocol, and the anti-quantum dynamic attribute-based encryption key fragments are distributed to the participants by adopting a threshold secret sharing technology. Threshold decryption and token verification are achieved through an alliance chain verification intelligent contract, an authorization record is generated, an access control strategy of an edge computing node is configured according to the authorization record, an oblivious transmission protocol is adopted to respond to data query, and an audit node monitors an access log, dynamically adjusts attribute weight parameters and synchronizes the attribute weight parameters to a key fragment.

The invention discloses an electric power communication analysis system and method based on big data, and the method comprises the steps: collecting multi-source heterogeneous data, carrying out the sensitivity grading, and generating labels; gathering the data to a big data platform, and completing storage, partitioning and index construction; an asynchronous main control chain mechanism is constructed, high-optimal data is dispatched for rapid anomaly judgment, and other data is processed in parallel; performing desensitization mapping on the high-sensitivity data to generate a short-time mapping bill and performing desensitization analysis; issuing a local task for the low-confidence exception, collecting backflow data, and verifying and determining a high-risk event; restoring the sensitive data in the authorization window, and destroying the bill and the secret key after abnormity analysis is completed; and triggering network regulation based on an analysis result, and recording the whole process to an audit log. By introducing an asynchronous scheduling and reversible desensitization mechanism, high-efficiency anomaly analysis and whole-process traceability of the electric power communication big data on the premise of ensuring safety and compliance are realized.

The invention relates to the technical field of information security management, and discloses an information security management method and system based on digital medical treatment. The method comprises the following steps: verifying doctor professional qualification, patient authorization range, data sensitivity level and time permission validity in a multi-institution medical data access request, and generating a permission verification result; analyzing ontology semantic attributes and sensitivity characteristics of medical search keywords input by a user, and determining a corresponding hierarchical encryption strategy based on the permission verification result; performing homomorphic encryption transformation on the medical term synonym set according to the hierarchical encryption strategy, and constructing a medical ciphertext database; and receiving a medical query request, executing symptom disease association matching and ciphertext state logical reasoning operation in the medical ciphertext database, and outputting an encrypted state search result. According to the method, the privacy leakage risk caused by search behavior trajectory analysis is effectively prevented, and the security and availability of medical data are improved.

The invention provides a multi-tenant-based centralized authentication and authorization method, system, device and medium, and belongs to the technical field of security and identity management, and the system comprises a unified portal layer, an authentication layer, an authorization layer, a strategy center and an audit monitoring layer. The unified portal layer receives a user request, identifies and injects a tenant identifier, and executes WAF rule verification, JWT signature verification and Token blacklist check; the authentication layer performs user or client credential verification on different accessed identity sources, generates and issues a JWT, and monitors the life cycle of a token; the authorization layer extracts an authority statement in the JWT and a locally cached strategy snapshot; the strategy center provides centralized storage, version management and visual editing of multi-tenant strategies; through cooperative work of each layer, accurate identification, unified authentication, centralized strategy management and comprehensive audit monitoring of tenants are realized. And the security, the expandability and the management efficiency of the system are effectively improved.

The invention provides a credible data space construction method and system based on data sharing, and relates to the technical field of data processing.The method comprises the steps that S1, in response to a request of a user for sharing target data, credible preprocessing is conducted on the target data to obtain credible data; s2, establishing a decision-making capability model for a user to autonomously perform credible authorization on the credible data; s3, analyzing a multi-dimensional sharing risk of the trusted data; s4, planning an optimal authorization auxiliary unit sequence based on the multi-dimensional sharing risk and the decision ability model; s5, in the process that the user autonomously performs credible authorization on the credible data, sequentially executing the authorization auxiliary units in the optimal authorization auxiliary unit sequence; and S6, aggregating the credible data subjected to credible authorization to construct a credible data space. According to the method, the credibility and the security in the data sharing process are remarkably improved, and the quality of the shared data and the protection of user privacy are ensured.

The invention discloses a multi-agent collaborative decision-making system and method based on knowledge Token, and the method comprises the following steps: S1, constructing a knowledge base architecture, executing the content Hash calculation, and generating an original fingerprint in an original fidelity layer; s2, extracting content, packaging the content into knowledge Token, and writing identification, semantics, source, authority, value, contract, association, traceability and health information; s3, activating a knowledge layer, constructing a vector index and mapping knowledge graph nodes; s4, unifying an index layer, matching task requirements, and screening and verifying candidate Tokens to obtain an authorization set; s5, the multiple agents generate local decisions and fuse values and semantics to form a collaborative result; and S6, binding a Token identifier after consistency verification, generating a collaborative decision and recording data consanguinity information. According to the method, multi-agent collaborative decision-making is realized through the knowledge Token and the knowledge graph, and the decision-making accuracy and traceability are improved.

The invention provides a large model dynamic protection method and system based on a zero-trust architecture. The method comprises the steps that a security proxy gateway receives an access request; authenticating an initiating main body of the access request, collecting context information and transmitting the context information to a strategy decision point; the strategy decision point calculates a trust score in real time based on a dynamic trust evaluation model and performs real-time evaluation in combination with an access control strategy to generate a dynamic authorization judgment result; if the access is allowed, forwarding the access request to a large language model server, and performing input security filtering; the large language model server generates response content and performs output security filtering; and returning the final response subjected to the output security filtering to the initiating main body through the security proxy gateway. According to the method, a multi-layer protection framework is constructed, a dynamic trust evaluation model is introduced, and a content filtering layer is deployed, so that continuous permission verification, risk adaptive control and full-link content security protection are realized, and the service security of a large model is effectively guaranteed.

The invention discloses an informatization system dynamic verification method based on a zero-trust architecture, and the method comprises the steps: collecting and standardizing user operation requests of all business systems, and achieving unified resource and organization identification; a distributed encryption operation log link is constructed through an end-to-end encryption protocol, and safe synchronization and tampering prevention of an operation behavior abstract are guaranteed; extracting a multi-dimensional right decision variable, inputting the multi-dimensional right decision variable into an adaptive artificial intelligence decision model, dynamically generating a reversible permission factor set, and supporting fine-grained and rollback permission authorization and real-time automatic revocation; the log chain is encrypted and recorded in the whole process, intelligent abnormity monitoring and end-to-end traceability are combined, the consistency and compliance auditing of the global permission state are supported, and the security, traceability and intelligent self-adaptive treatment capacity of sensitive operation in the multi-organization cooperation environment are effectively improved.

Methods, systems, and devices for wireless communications are described. A first network entity of a first service provider may obtain, from a first user equipment (UE), an invite message for initiating a call between with a second UE that includes an identity associated with the first UE and an authorization server. Based on whether the first UE is subscribed to a third-party information service, the first network entity may obtain third-party information from the authorization server. The first network entity may output the invite message to a second network entity of a second service provider, where the invite message output by the first network entity includes the third-party information in accordance with whether the third-party information is obtained. Based on whether the second UE is subscribed to a third-party information verification service, the second network entity may verify the third-party information and output the invite message to the second UE.

A retrieval-augmented generation method for a large language model receives a user query and generates a vector embedding of the user query. The vector embedding of the user query is stored in an embedding vectors space. Also stored in the embedding vectors space are embeddings of documents retrieved from a corpus of information / A retrieval-based artificial intelligence (Al) model identifies which documents are relevant to the user query according to a similarity measure applied to the vector embedding of the user query and the vector embeddings of the documents. The generative Al model receives the user query and the documents identified as relevant to the user query and generates new content, based on the user query and the documents identified as relevant to the user query.

The invention provides a multi-modal data desensitization method, system and device and a medium, and belongs to the technical field of information security. The method comprises the following steps: firstly, acquiring multi-modal original data based on preset access information and acquisition frequency, and after standardized preprocessing, positioning sensitive information by using a classification recognition algorithm and generating an analysis report. Then, according to a report, matching a strategy from a desensitization strategy library bound with the sensitivity level, adjusting a dynamic confusion algorithm parameter to desensitize, integrating and generating desensitized multi-modal data, and recording and storing a mapping relationship between the original data and the desensitized data; and if a restoration request is received, after authorization verification is passed, reverse desensitization restoration data is carried out by using the mapping relation. Besides, full-process feedback information is collected, the desensitization effect is quantitatively evaluated according to a preset index, the desensitization strategy and algorithm are iteratively optimized accordingly, and effective desensitization and safety management of multi-modal data are achieved.

A computer-security architecture removes activation authority from client-facing purchase flows. A server records a digital entitlement in an INACTIVE state and issues a presentation artifact. A verification service accepts messages only from trusted origins carrying freshness-bounded evidence and validates using (i) stateless keyed recomputation over a time-windowed payload, (ii) confirmation that token-rail authorization data maps to a registered association within a policy freshness bound, or (iii) a server-maintained session. Activation occurs only on an authoritative commit path that enforces no activation without a durable audit record and effective-once behavior: either a single ACID transaction that conditionally updates state and writes an insert-only audit in the same commit, or an append-only activation ledger with idempotent materialization. Access controls deny issuance-facing code permission to set ACTIVE. Expiration is timer-free via batch or TTL evaluation.

The invention belongs to the technical field of network security, and relates to a terminal security access control method and device, computer equipment and a storage medium, the method comprises the following steps: deploying an infrastructure for terminal security access, the infrastructure comprising a client, a security system and a server component; the method comprises the following steps: performing initial registration on terminal equipment, and realizing unique binding of a terminal identity and loading of a basic security policy by acquiring an equipment fingerprint, issuing a certificate and configuring a policy; the user identity and the equipment credibility are verified in real time through a multi-factor dynamic authentication mechanism; through signature verification and encrypted transmission, application and network communication authentication is carried out, and application legality, communication channel security and operation environment credibility are ensured; and after the authentication is passed, trusted connection is established, fine-grained authorization is implemented, and security isolation of a service layer is realized through dynamic token and API management and control. The problems that in existing terminal access control, the authentication dimension is single, the authorization granularity is rough, and dynamic management and control are lacked are effectively solved.

A system and method are disclosed for tracking and verifying authenticity, loss, fraud, or unauthorized use of assets within a supply chain. The method includes scanning a multimodal tag (e.g., QR code and NFC tag) associated with an asset to generate scan data comprising a hash code, asset identifier, and verification URL. The scan data is transmitted to an application server of a parent organization, where a controller retrieves associated location and organization identifiers. The controller determines authorization status, compares the hash code with reference values in a verification database, and performs authenticity checks to classify the asset as genuine, lost, duplicated, or pirated. The system integrates with a CRM platform to register new child organizations using data synchronization objects comprising payloads, callout instructions, and error handling. AI-based analysis may detect route deviations, fraudulent insertions, or asset misuse patterns based on route history and scanning behavior.

The invention relates to a big data security management system, and provides a security management system covering a whole life cycle aiming at the problems of untrusted source end, link leakage, centralized storage of single points, extensive authorization, disposal lag and the like. The system comprises an acquisition security module, a transmission encryption module, a storage security module, an access control module, a threat detection module, a situation awareness module, a traceability module and an emergency response module. A session basis is generated through multi-factor authentication, a dynamic key is derived according to time slices, and data fragments are encrypted one by one; distributed storage is adopted, and metadata is chained to be non-tampered; implementing fine-grained authorization by taking the attribute as a core; utilizing a sequence model linkage knowledge graph to identify abnormity and calculate a risk index; and when the threshold is exceeded, automatically reconstructing a log chain and executing isolation, alarm or recording. According to the system, trusted acquisition, confidential transmission, traceable storage, fine authorization and automatic disposal are realized, and the safety and compliance are remarkably improved.

The invention relates to the technical field of computers, in particular to a data sharing management system and method for a database, and the system comprises an identity verification module, a permission adaptation and grading approval module, a risk control module and an iteration module, and the method correspondingly executes the functions of the modules. The identity verification guarantees the legality of an access subject through format verification and multi-dimensional hierarchical authentication, and the intensity of the hierarchical authentication is dynamically adjusted along with the data sensitivity; authority management and control execute differentiation logic according to public, internal and confidential three levels, and fine authorization is achieved; the risk control module monitors abnormal operation in real time and performs grading processing; all operations are recorded in a block chain audit log, and the system realizes dynamic iteration through regular verification and historical data optimization. The data sharing security and cooperation efficiency are considered, the risk controllability and the system adaptability are improved, and the multi-scene data sharing requirements such as enterprise cross-department and external cooperation are met.

The invention discloses a large model corpus data interaction system and method based on a trusted execution environment, a terminal and a medium. The system comprises a data provider, a data demander and a trusted data space service platform. And the data provider is used for encrypting the corpus data, and performing preprocessing, directory sorting and packaging on the corpus data in the data provider connector to obtain the data capsule. And the data demander is used for submitting a calculation task in the data demander connector and obtaining corpus data of the data capsule for calculation after authorization. And the trusted data space service platform is used for storing the encrypted corpus data, controlling access of a data user, scheduling a calculation task, managing a key and generating an audit log. Through trusted execution environment hardware isolation and full-link encryption, it is ensured that corpus data only exists in a plaintext form in the trusted execution environment in the full life cycle from access to destruction, and unauthorized access and leakage are completely eradicated.

Embodiments provide artificial intelligence methods and systems for evaluating vulnerability risks of issuer authorization system. Method performed by a server system includes accessing a set of payment transaction data including subset of fraudulent transaction data. Method includes generating via a machine learning model, set of synthetic transaction data based on the subset of fraudulent transaction data. Method includes accessing set of historical card velocity features and collating the set of synthetic transaction data and the set of historical card velocity features to generate set of enriched synthetic transaction data. Method includes extracting via a classifier, subset of feasible fraudulent transaction data from the set of enriched synthetic transaction data. Method includes generating simulated authorization model based on the set of payment transaction data. Method includes classifying via simulated authorization model, each enriched synthetic transaction from the subset of feasible fraudulent transaction data as one of fraudulent transaction and non-fraudulent transaction.

A method for microservice authentication includes intercepting, at a first policy engine sidecar of a first microservice, a service request from the first microservice to a second microservice. The service request includes services requested from the second microservice. The method includes generating a transaction challenge, transmitting the service request, a first token identifying the first microservice, and the transaction challenge to the second microservice, and intercepting a service request response from the second microservice to the first microservice. The method includes determining whether the service request response includes a second token identifying the second microservice and a transaction challenge response generated by a second policy engine sidecar of the second microservice, and transmitting the service request response to the first microservice in response to determining the second token identifies the second microservice and determining that the transaction challenge response includes an acceptable transaction challenge response.

The invention relates to the technical field of block chains, in particular to a block chain multi-platform data credible management method and system based on a user portrait, and the method comprises the steps: carrying out the multi-platform data collection, obtaining a plurality of original user data sets, carrying out the encryption processing of the original user data sets, obtaining an encrypted user data set, carrying out the block packaging processing of the encrypted user data set, and carrying out the block packaging processing of the encrypted user data set. Performing consensus verification on the block to be subjected to consensus encryption to obtain an on-chain encryption block; performing feature extraction on the on-chain encryption block to obtain a user feature data set; performing feature division on the user feature data set to obtain a user feature type set; performing portrait construction based on the user feature type set to obtain a user portrait; and obtaining a portrait access standard, and according to the portrait access standard, performing authorization judgment by using the data access authorization unit. According to the method and the device, the problem of low data credibility in the current management process of the multi-platform data of the block chain can be solved.

The invention belongs to the technical field of intelligent safety supervision, and particularly relates to a coal mine personnel safety behavior analysis method, which synchronously associates a management instruction, personnel behavior data, an equipment state and environment parameters according to timestamps through a management platform, obtains the current position of a personnel in real time, dynamically judges whether the personnel moves correctly or not, and improves the safety of the personnel. When a person approaches each maintenance position, automatically checking whether the maintenance position has omission or not, if the omission is found, generating a rechecking instruction in real time and pausing subsequent operation authorization, if the omission is not found, carrying out consistency checking on the operation sequence, the operation video content and the standard regulation, and if the checking does not reach the standard, carrying out rechecking on the operation video content and the standard regulation; if yes, second-level early warning is triggered immediately, a recheck mechanism is started, subsequent operation authorization is paused by dynamically monitoring operation compliance and combining authority control, personnel are prevented from entering a subsequent maintenance position with an illegal state, and the problem of multi-position continuous violation which can only be traced afterwards in an existing method is thoroughly solved.

The invention provides an AI model management method and system based on dynamic NFT, and the method comprises the steps: firstly packaging the core elements of an AI model into on-chain intelligent assets through the dynamic NFT, and achieving the clear definition and credible storage of the ownership of the model; then, a programmable smart contract bound with the dynamic NFT is utilized to support flexible definition of an atomization authorization rule, and traditional fragile API key authorization is replaced; and finally, forcibly recording a father-son relationship in a model iteration process through a dynamic NFT chain derivation mechanism to form a non-tampering version pedigree map, and solving the problems of attribution dispute and technical source tracing of the fine tuning model. According to the invention, property right clarification, authorization control flexibility and version management credibility of AI model digital assets are realized, and the method is suitable for transaction, circulation and governance scenes of AI assets such as large language models and vertical field special models.

The invention discloses a monorail crane multi-vehicle cooperative scheduling control method based on edge calculation, which comprises the following steps: carrying out topological modeling on a track, and constructing a section-time slice space-time resource model; acquiring real-time operation data of each vehicle at an edge computing node, generating a vehicle state set and executing time-space conflict prediction; when a multi-vehicle potential conflict is detected, carrying out topology consistency check on a conflict section; calculating a priority value of each vehicle in the corrected candidate traffic relation; performing section occupation authorization and shadow time slot distribution through a double-threshold mechanism; the node issues an operation instruction to the authorized vehicle; when abnormal events such as communication interruption, retention or task insertion are detected, the node triggers local path replanning and occupancy right redistribution. According to the method, a multi-factor priority scheduling mechanism is introduced into the edge computing node, so that real-time conflict avoidance and self-adaptive cooperative control of multiple monorail cranes is realized.