75 results about "Role-based access control" patented technology

A system for improving employee engagement and automating the integration of business processes. The system includes: a user interaction module configured to receive multimodal inputs, including natural language text and voice requests from employees via enterprise portals, mobile applications, voice-activated devices, and collaboration platforms, and to generate real-time responses via conversational output channels; a context processor that is operationally coupled with the user interaction module, wherein the context processor stores the interaction history, employee preferences, organizational role metadata, and task results in both short-term and long-term memory and dynamically derives context for controlling responses and initiating workflows; A natural language and intent processor that is communicatively linked to the context processor. The intent engine consists of large language models trained on company-specific lexicons to perform intent detection, entity extraction, ambiguity resolution, and sentiment or urgency classification from employee queries; a workflow orchestration layer in communication with the intent engine and the context processor, wherein the workflow orchestration layer includes a rule-based and AI-powered process execution engine configured to automatically initiate, route, and complete cross-functional business tasks, including approvals, escalations, and compliance checks, with workflows defined using modular templates that include conditional logic and time-based triggers; Webhooks and authentication protocols provide secure interoperability between the workflow orchestration layer and external enterprise platforms; a feedback and learning module that is operationally coupled with the workflow orchestration layer and the natural language understanding engine, wherein the feedback and learning module is configured to analyze task completion rates, response accuracy, latency metrics, and user feedback signals, and to retrain underlying language and workflow models for adaptive improvement in real time; and an administration console with role-based access controls, compliance dashboards, audit trails and interfaces for workflow configuration, whereby the administration console enables authorized personnel to monitor system operations, adjust interaction rules and enforce data protection restrictions across departments.

The invention discloses a database management method and management system, and relates to the technical field of general database management, and the system comprises a user information management module, a work management module, a salary settlement module, an evaluation feedback module, an analysis prediction module, a multi-terminal integration module and a safety guarantee module. In the invention, a role-based access control permission model is constructed in a permission control layer and a module definition, and a field-level data control mechanism is implemented for three roles of a platform administrator, a customer enterprise and an employee, for example, the employee can only check a specific public field in a salary list, and sensitive fields such as a salary calculation formula are dynamically shielded; through a permission inheritance mechanism, the system automatically adds a filtering condition that employee ID = current user ID for a query request of an employee role, data isolation is ensured, a multi-dimensional data relation graph of employee-post-customer-contract is constructed, and a dynamic association path between entities is mapped in real time through a visual view.

Examples analyze effective permissions in a role-based access control system. A prompt is created for a large language model (LLM). The prompt includes a role definition for a role of a role-based access control system, and action definitions. The role definition for the role includes an action and effective permissions text describing a summary of permission limitations provided by the role. The action definitions are provided in a hierarchical format. Query text is added to the prompt. The query text includes a question about effective permissions associated with the role. The prompt is submitted to the LLM, thereby generating response text from the LLM. The response text is displayed to a user.

The invention provides a multi-party data collaborative exchange method, system and device, a medium and a product, and belongs to the technical field of data information processing, and the method comprises the steps: in a data exchange process, after identity authentication of participants of data exchange is passed in a trusted space, carrying out the dynamic verification of the access authority of the participants based on the real-time attributes of the participants; under the condition that the dynamic verification is passed, executing data exchange in the trusted space to obtain a data exchange result; sending the data exchange result to a data decryption party corresponding to the data user, so that the data decryption party decrypts the data exchange result; wherein the real-time attributes of the participants comprise real-time environment attributes, behavior attributes of the participants and static attributes of the participants. When the access permission is verified, transition from role-based access control to behavior-based access control is realized on the basis of dynamic combination of multi-dimensional attributes, and dynamic control on the access permission is realized on the aspect of finer granularity.

A method for role-based access control recommendation includes obtaining one or more security logs from a security analytics platform. The method includes determining access rights to the one or more security logs for one or more users of the security analytics platform. The determining includes generating one or more clusters of security logs based on the one or more security logs. The determining includes providing, to a user of the security analytics platform, a recommendation for a first data access group for the security analytics platform based on a first cluster of the one or more clusters. The determining includes, responsive to input from the user of the security analytics platform, generating the first data access group for the security analytics platform based on the first cluster of the one or more clusters.

A computer-implemented system (100) for real-time detection of supply chain disruptions and forecasting of the financial impact in a computer-driven ERP environment, wherein the system (100) comprises: a data acquisition interface (1) configured to continuously capture structured and unstructured operational data from one or more ERP modules, supply chain execution systems, and enterprise event streams; a data management and harmonization engine (2) configured to validate, normalize, deduplicate and semantically map the captured data into a unified, time-aligned canonical enterprise schema; a disturbance signal fusion and anomaly detection engine (3) configured to fuse signals from multiple sources and detect disturbance events using one or more machine learning models to output a disturbance value, event class and a list of affected nodes; a supply chain dependency graph and a digital twin builder (4) configured to create and update a dynamic dependency graph representing suppliers, facilities, transportation routes, SKUs, orders, contracts and lead times, and propagate disruption effects across the graph; a financial impact forecasting engine (5) configured to estimate the real-time and forward-looking effects of the disruption on one or more financial measures, including sales, margin, working capital, cash flow, service level penalties and inventory holding costs, and furthermore the effects on the cost of goods sold (COGS) and / or the landed costs using a Kl-based forecast with a range of uncertainty; a module for coordinating corrective actions and automating workflows (6) configured to generate ranked corrective actions and initiate ERP workflow steps, including reordering, reassignment, alternative sources of supply, production rescheduling and logistics diversions, wherein the ranked corrective actions include recommendations to resolve the disruption by using available stock, reassigning low-priority shipments or diverting shipments that can be delivered later within a lead time window; an explainability, audit trail and compliance logging module (7) configured to record model inputs, feature assignments, decision justifications, scenario assumptions and action results as an immutable audit trail; and a visualization, alerting and collaboration interface (8) configured to output real-time alerts, dashboards and scenario comparisons to authorized users and downstream systems via APIs and role-based access controls, wherein the interface (8) generates a quick report view that displays early disruption signals and impact on manufacturing costs, delivers notifications to mobile devices, triggers a special urgent notification if the disruption affects a high-priority trading partner, and accepts user responses on mobile devices that automatically and without delay trigger corrective actions or updates in the ERP system.

Disclosed are various embodiments for multi-domain, role-based access control (RBAC) using large language models. Various embodiments can receive an access request from a client device associated with a user. Various embodiments can then send a prompt to identify a user role for the user to an agent of a machine learning model. Various embodiments can receive the user role for the user from the agent. The various embodiments can determine the capability for the user to access a resource by comparing the user role for the user to allowed user roles for the resource. Various embodiments can then send an access response to the client device that indicates whether the user can access the resource.

A system for event-driven distributed data network analysis, the system includes: a multitude of domain data nodes, each comprising a stream storage, a multitude of transformation pods, and a product API, with each domain data node ingesting heterogeneous event streams, validating schema compliance, performing enrichments, and making data products available under versioned schema contracts; each domain data node further comprises a hardware-based edge intelligence appliance comprising an enclosure, a compute module with heterogeneous processing units selected from CPUs, GPUs, and TPUs, a secure enclave module for confidential execution of transformation code on encrypted data, a protocol-structured stream storage medium supporting multi-level retention, and industrial I / O interfaces configured for direct interaction with sensors, programmable logic controllers, and cloud-native services; an event mesh backbone processor configured to connect the multitude of domain data nodes via a publish-subscribe architecture, with the backbone guaranteeing exactly one-time delivery, partition-level sorting, and geo-replicated durability; a Contextual Intelligence Engine coupled with the Event Mesh Backbone processor, the engine comprising a semantic graph memory and a Streaming Graph Reasoner configured to map raw events into an ontology, perform graph joins in real time, and recognize composite causal patterns across multiple domain data nodes; a governance and policy control unit integrated into both the data and control layers. This layer enforces zero-trust security, role-based access control, real-time provenance tracking, and regulatory compliance; and An actuation interface coupled with the contextual intelligence engine and the governance layer. The actuation interface is configured to generate control commands for operational technology devices and digital workflows, thus closing the loop from data acquisition to autonomous decision-making.

The invention discloses a data desensitization display method and device. The method comprises the following steps: in response to a display request of to-be-displayed data sent by a target object, obtaining a biological feature vector of the target object at the current moment; target data is obtained, and the target data is obtained after the to-be-displayed data is encrypted; after the biological feature vector of the target object at the current moment is successfully authenticated, determining an encryption seed of the target object according to the biological feature vector of the target object at the current moment and pre-stored auxiliary data; generating a private key based on the encryption seed; and decrypting the target data by using the private key, and displaying the to-be-displayed data obtained after decryption. The method provided by the invention at least solves the technical problem that the display mode is single due to the fact that the data is displayed in a role-based access control mode in related technologies.

A telemetry processing system in a cluster network generates telemetry data from a plurality of telemetry producers and formats it into a structured format for storage. Producers define new metrics for use in a running network. Role-based access control (RBAC) levels for metrics are mapped to users based on roles within an organization using the produced telemetry data. A final RBAC level of a new metric is established through a recommendation and validation process between the producer and an RBAC recommendation module. Once validated, the final RBAC level and new metric are stored in a telemetry catalog. Telemetry datasets for the new metric are sent for storage and transmitted to appropriate users based on RBAC rules including the final RBAC level.

An object access service is implemented on a computer system for configuring and enforcing multi-dimensional data security using security assignments beyond role-based access controls. The computer system accesses a request submitted on behalf of a user for access to database structure(s). The computer system requests predicate(s) mapped to role(s) assigned to the user and stored in association with the database structure(s). Predicate(s) submitted to the database may be dynamically filled in by the database pursuant to retrieving data from the database structure(s) to reference security assignment field(s) and security assignment value(s) of the security assignment. The predicate(s) are used to retrieve a security assignment that restricts access to the database structure(s) beyond the role(s) assigned to the user. The security assignment is used to restrict data accessible from the database structure(s) to generate a result set, which is transmitted to a client consumer system for consumption via a consumer interface.

The invention provides a POS application security signature system and method based on cloud service. The system architecture is clearly divided into a front-end service area and a high-security trusted area. The front-end service area is deployed in a special network management area which is logically isolated from the Internet and comprises a Web management background and a Web management background database; the high-security trusted area is a trusted environment, and an application signature server, an application signature server database and a hardware security module are deployed in the high-security trusted area. An application developer accesses the system through a controlled client environment. According to the method, responsibility separation of a submitter, a security officer and a key administrator is realized through role-based access control, hierarchical strong identity authentication is adopted, and a rigorous process is followed; a submitter verifies the hash of a file and then creates a task, the task data is synchronized to a high-security credible area after two security officers approve the task independently in sequence, and two key administrators execute dual control to start an HSM key to complete signature. The whole process operation is recorded in an auditing log which cannot be tampered. According to the invention, automation, high security and compliance of the cloud signature process are realized.

The application discloses a kind of industrial internet of things multi-key fuzzy search method based on Walsh matrix, comprising the following steps: S1, system initialization is carried out;S2, based on system initialization result, key distribution is carried out;S3, based on key distribution result, generate ciphertext index;S4, based on key distribution result, generate security query trapdoor;S5, according to ciphertext index and security query trapdoor, carry out ciphertext matching and authorized interception.The application realizes the bottom unification of retrieval and access control, effectively resists structured information disclosure attack, and seamlessly nests the polynomial coefficient of role-based access control into the data structure of encryption matrix.

The technology disclosed herein enables the reduction of unused, or excess, access permissions in roles assigned to users. In a particular example, a method includes identifying access permissions used by a user and applying a greedy algorithm to select a set of roles from a plurality of roles available for role-based access control (RBAC) to enable the access permissions. Each iteration of the greedy algorithm selects a different role for inclusion the set of roles based on a blast radius of the different role. The method further includes assigning the set of roles to the user; and enforcing the access permissions granted by the set of roles.

Disclosed herein are system, method, and computer program product embodiments for creating a tailored access profile for improving the security of an access control system. An embodiment operates by extracting application access requirements for a role from a role description using a first large language model. The embodiment then generates an embedding corresponding to the application access requirements using a second large language model. The embodiment then searches for a first access profile in a data store based on the embedding. The embodiment then generates a second access profile based on the application access requirements using the first large language model. The embodiment then selects the first access profile or the second access profile based on the application access requirements. The embodiment finally tailors the selected access profile based on feedback, thereby creating the tailored access profile.

A quantum computing system receives, from a requestor, a first access request that identifies a subject, an action, and a resource. A mapping structure that identifies a plurality of qubits that are in superposition and encoded with a plurality of rules that govern access to the resource is accessed. Based on the mapping structure it is determined that a set of qubits of the plurality of qubits applies to the access request. Data encoded in the set of qubits or a reference to each qubit in the set of qubits is provided to the requestor.

The invention provides an intelligent finance and tax auditing system and method based on a block chain, and relates to the technical field of finance and tax auditing. The system comprises a block chain underlying architecture, a data encryption module, an access control module, an intelligent contract module, a private key management module and an audit application interface. And the block chain bottom layer architecture adopts a permission system block chain network, so that tampering resistance and traceability of finance and taxation data are ensured. And the data encryption module is combined with symmetric and asymmetric encryption algorithms to protect the security of enterprise sensitive finance and tax data. The access control module implements a role-based access control mechanism, integrates multi-factor authentication, and records an audit log on a block chain. According to the invention, through comprehensive application of the block chain, the encryption technology, the smart contract and other means, the problems of data security, privacy protection, smart contract vulnerability and private key management in traditional finance and taxation auditing are effectively solved, and the efficiency and accuracy of finance and taxation auditing are significantly improved.

The invention discloses a multi-tenant architecture SAAS vehicle management system, and belongs to the technical field of SAAS systems and vehicle management. Aiming at the problems that a traditional localized vehicle management system is high in deployment cost and poor in data isolation and an existing SAAS system is insufficient in adaptability, the system adopts a layered architecture design: an infrastructure layer realizes elastic deployment based on a Docker container; the data storage layer adopts a MySQL5.7 database, and realizes data logic isolation through tenant IDs; the core service layer integrates customized modules of vehicle scheduling, data acquisition and the like, and can automatically generate a maintenance plan and dynamically schedule vehicles. The authority management layer adopts an RBAC (Role Based Access Control) mechanism to realize refined authority distribution; the front-end interaction layer supports browser and applet zero-deployment access; and the operation platform overall plans operation and maintenance and security assurance. According to the method, hardware deployment and IT maintenance of enterprises are not needed, the use cost can be reduced, data isolation is safe and reliable, the vehicle scheduling response speed is increased, and the method can meet the requirements of multiple industries such as logistics and engineering.

A computer-implemented system and method for administrating human biospecimen collection facilitates secure, de-identified coordination among donors, scientists, and administrators through a modular digital interface. The system enables administrators to manage project dashboards, assign donor identities to sample jobs, initiate and track collections, configure lab and location settings, and process payments using integrated financial services. Scientists can create, schedule, and monitor biospecimen requests, set donor inclusion criteria, and manage sample delivery. Donors can register, undergo identity verification, opt in to sample types, and track donation history. The platform supports automated notifications, real-time courier tracking, configurable appointment durations, and differential compensation models. Technical benefits include enhanced data integrity via role-based access control, improved efficiency through integrated scheduling and payment APIs, and reduced administrative burden via automated matching and logistics coordination. The system provides compliance with privacy standards while enabling scalable, institution-specific or marketplace-based biospecimen acquisition.

Systems and methods for enforcing granular access controls in large language models. The system can receive a user query, and an access token associated with an access profile. The method includes ingesting, by a machine-learned metamodel, the user query and the access token. The machine-learned metamodel can be configured to compare the access profile with one or more topics, wherein the one or more topics are associated with data source permissions and based on the comparison, retrieve data associated with the one or more topics. The method includes receiving, by a machine-learned model, the user query, the access token, and the data associated with the one or more topics. The method includes generating, by the machine-learned model, a query response, wherein the query response includes a response comprising the one or more topics that are filtered according to the access profile and the data source permissions.

Systems and methods receive an access request for a knowledge domain framework for generative AI model development, the access request including user credentials, and filter, based on the user credentials being authenticated, permissions defining a user-specific access level for utilizing the knowledge domain framework. Display of a user interface that includes prompts facilitating inputs to the knowledge domain framework is initiated, the prompts being regulated based on the permissions. Information to establish a desired knowledge domain is received from a user device associated with the user interface, the desired knowledge domain including a corpus of selected documents, and an indication of a type of a generative artificial intelligence model to be developed is received from the user device. Display of a prompt template for receiving user inputs and providing generative outputs is initiated, and text submission(s) are received. Response(s) to the text submission(s) are generated.

For role-based content adaptation, a set of predefined user roles and role-based transformation instructions are obtained from the role-based access control system. The role-based transformation instructions define content adaptation rules for each of the roles. Then, a large language model is used to transform the input content for each of the obtained roles, creating a role-based adapted content instance of the input content. The large language model is used to retrieve role-related content from the input content using the role-based transformation instructions. The role-based adapted content instances are stored in a role-partitioned content storage, where each instance is tagged to identify the associated role. Through role-aware content partitioning, various content types can be managed efficiently.

Systems and methods receive an access request for a knowledge domain framework for generative AI model development, the access request including user credentials, and filter, based on the user credentials being authenticated, permissions defining a user-specific access level for utilizing the knowledge domain framework. Display of a user interface that includes prompts facilitating inputs to the knowledge domain framework is initiated, the prompts being regulated based on the permissions. Information to establish a desired knowledge domain is received from a user device associated with the user interface, the desired knowledge domain including a corpus of selected documents, and an indication of a type of a generative artificial intelligence model to be developed is received from the user device. Display of a prompt template for receiving user inputs and providing generative outputs is initiated, and text submission(s) are received. Response(s) to the text submission(s) are generated.

The invention relates to the technical field of industrial manufacturing informatization, in particular to a test fixture management system. The intelligent test fixture management system realizes full-life-cycle management of a fixture through the dynamic role-based access control authority mechanism, the intelligent conflict detection algorithm and the chain log mechanism, wherein a log data packet generated by the log management module comprises log entries, cryptographic hash values and preorder hash values. Through a dynamic role-based access control authority mechanism, functional level operation isolation of three layers of role super administrators / department administrators / production line personnel is realized. And the authority verification unit intercepts unauthorized operation in real time, and updates the cache in combination with message queue broadcast when the authority is changed, so that the occurrence rate of system unauthorized operation is reduced to 0.3 per year from 23 per year in the industry on average, and the requirement of a security standard on authority control is met.

Systems and methods receive an input selecting functions for inclusion during creation of agentic large language model(s) (LLM), the functions being defined in accordance with role-based access controls (RBACs) provide an operative connection to existing LLM(s) to be included in a customized knowledge domain framework. Further, instructions on use and deployment to be included as selectable metadata for establishing guardrails for the agentic LLM(s) are obtained, where the guardrails establish rules for integration and use of the agentic LLM(s). Parser(s) for selection to be applied to the agentic LLM(s) are established. Selection of prompt template(s) for structuring user inputs and model outputs for the agentic LLM(s) is facilitated, and an operative connection to existing agentic LLM(s) for selection is provided. Further, access to existing validation large language model(s) is provided for selection.

A metadata-driven enterprise data architecture system for automated data collection, processing, and reporting, consisting of: a centralized metadata control repository configured to store canonical enterprise data models and business semantic definitions, source-destination mapping rules and transformation logic, data quality thresholds and matching parameters, governance policies and compliance controls, data provenance relationships and audit tracking rules, security and access control configurations, planning instructions and reporting specifications; an execution and orchestration engine that is operationally connected to the metadata control repository and configured to dynamically interpret metadata definitions, automatically implements data ingestion pipelines to extract data from legacy systems, cloud platforms, application interfaces, files, and streaming sources, performs transformation operations such as normalization, enrichment, deduplication, aggregation, and format harmonization to align the ingested data with the canonical enterprise data model, applies metadata-driven data quality validation, exception handling, and reconciliation processes to ensure accuracy and consistency, and enforces metadata-defined security policies, including role-based access control, encryption, and data masking.Automatic capture of complete data provenance and audit records across all processing stages and creation of standardized operational, analytical, and regulatory reports based on metadata-defined reporting structures and business metrics; where changes to metadata definitions automatically modify the collection, processing, governance, security, and reporting behavior without requiring manual redesign of data pipelines or application code.

Adaptive energy management system and method based on tokenized energy profiles (TEP) in a distribution network, comprising a data ingestion module configured to acquire, aggregate and encrypt structured and unstructured data in real time; a real-time intelligent analysis module based on neural networks and configured to detect patterns of energy consumption and generation, to classify these patterns by generating energy footprints associated with one or multiple users, to predict consumption or generation values and to obtain optimization actions in real time; an automated control and activation module configured to control elements of electricity generation and consumption using model-based predictive control (MPC) techniques and fuzzy algorithms; and a security module configured to encrypt communications using encryption techniques, role-based access control (RBAC), blockchain storage, and real-time monitoring of anomalies.

A telemetry processing system in a cluster network generates telemetry data from a plurality of telemetry producers and formats it into a structured format for storage in a datastore. Users of the telemetry data are mapped to specific role-based access control (RBAC) rules per an identity and management (LAM) module. This mapping is stored in a dynamic RBAC-based telemetry catalog for further rules checking as telemetry data is generated. This adds a second layer above user subscription terms to safeguard the security of telemetry data based on RBAC rules, and allows the system to define conditions under which certain users can receive certain types of telemetry data in an efficient and dynamic manner.

The application discloses a kind of supervisory remote check portal systems, belong to clinical trial supervision check field.The application includes: remote access module (L23), provides safe remote access portal for regulatory agency (FDA, EMA, NMPA);Data viewing module (L24), support real-time viewing source data (EDC / CRF / laboratory data), audit tracking record (data creation / modification / deletion record and operation time stamp / user), eTMF document (clinical trial scheme / informed consent / researcher manual / ethics batch piece);Access control module (L25), provide role-based access control, data access range isolation, operation permission control, IP white list;Log module (L26), record all operations;Evidence download module (L27), support downloading check evidence.The application realizes the safe compliance supervisory remote check, and check time is shortened from average 5 days to 1 day, and travel cost is reduced by 95%.