10 results about "Privacy rule" patented technology

Techniques for maintaining geographic-based data privacy rules in networked environments. An example method includes receiving, from a first subsystem, a query for data; receiving, from the first subsystem, an aggregate passport indicating at least one geographic region in which the first subsystem and at least one second subsystem connected to the first subsystem operates; and determining that the at least one geographic region complies with at least one data privacy rule that applies to the entity. Based on determining that the at least one geographic region complies with the at least one data privacy rule that applies to the entity, the example method further includes transmitting, to the first subsystem, at least a portion of the data; and storing an indication that the at least the portion of the data has been shared.

A privacy-preserving retail monitoring system employing symbolic artificial intelligence for non-identifying behavioral analysis is disclosed. The system includes a 360-degree multimodal sensing assembly configured to capture optical, thermal, acoustic, and depth data, an onboard symbolic execution kernel that converts sensor input into non-biometric behavioral glyphs, and a consent-governed classification module enforcing role-based and jurisdiction-specific privacy rules. Behavioral events are evaluated through a programmable policy directed acyclic graph, enabling real-time redaction, escalation, or suppression without generating facial recognition, identity vectors, or raw audio transcripts. A hardware-enforced redaction subcircuit blocks non-compliant outputs from storage or transmission, while encrypted audit trails capture only symbolic paths and consent states. The system executes fully at the edge, supports compliance replay capsules, and outputs redacted analytics suitable for safety, loss prevention, and operational analysis. Modular installation formats permit deployment across retail, convenience, and fuel environments as a drop-in replacement for legacy surveillance hardware.

The disclosure provides a privacy data processing method and device, electronic equipment and readable storage medium, relates to the technical field of computers, in particular to the technical field of mobile platform technology, application development and the like. The specific implementation scheme is as follows: a plurality of privacy application programming interfaces are configured according to a preset privacy rule; each privacy application programming interface corresponds to at least one function function, and the function function of the function function is to process privacy data; the plurality of configured privacy application programming interfaces are encapsulated to generate a calling application programming interface for calling by an application function module.

Methods, systems, and apparatus are described providing networking engines. Specifically, the present specification relates to a method for implementing software containers implementing network engines that may be configured to act in a zero-knowledge environment. In such implementations, all information pertaining to the network engine associated with a user that is stored in the container is solely that of a user unless explicitly shared by the user. In some implementations, the containers may be configured to participate in a publish-and-subscribe network in order to share information. In addition, the containers may be provisioned with controls so that global operators may comply with local privacy rules.

This invention discloses a blockchain-based method and system for managing the privacy and security of medical information. The method includes: authenticating institutional nodes and allocating permissions through a multi-chain collaborative mechanism; employing lightweight encryption algorithms to implement layered encryption of medical information with different sensitivity levels; constructing a unified privacy rule adaptation system using a cross-institutional privacy collaborative governance model and smart contracts; distributing the encrypted data to multi-chain nodes after sharding; collecting full-lifecycle operation data through a medical privacy traceability platform to generate tamper-proof traceability logs; and combining privacy and security management parameters with a multi-chain collaborative verification mechanism to analyze the logs in real time, identify abnormal behaviors, and trigger corresponding control responses. This invention integrates multiple technical modules to form a closed-loop management system, achieving compliance and security in cross-institutional sharing of medical information and providing an efficient solution for protecting medical information privacy.

The invention discloses a data reporting method, a data reporting device, electronic equipment and a storage medium, and belongs to the technical field of data processing. The method comprises the following steps: acquiring multi-dimensional feature information, which is acquired in real time through a multi-modal identification interface, of an equipment mainboard; initiating a matching request for matching a plug-in to a cloud function plug-in library according to the multi-dimensional feature information; receiving an encrypted plug-in package returned by the cloud for the matching request; requesting a filtering rule table and / or a noise configuration table from a cloud based on the plug-in packet; and reporting the device data of the target device according to the filtering rule table and / or the noise configuration table. According to the embodiment of the invention, the plug-in package is downloaded, the function label of the plug-in package is analyzed and the privacy rule is associated according to the equipment requirement, flexible updating can be guaranteed by separating the plug-in from the rule, meanwhile, the data reporting amount can be reduced, and data availability and privacy protection are considered.

The invention relates to the field of health data management, and provides an intelligent cloud database management method and system based on multi-modal health data. Task requests are obtained, and strict verification and security review are carried out; creating a logically isolated execution environment in the cloud database system, and scheduling local computing resources in the environment to execute computing tasks; and desensitizing the intermediate result according to a preset privacy rule, generating a final calculation result, and sending the final calculation result, thereby realizing balance between data privacy protection and data availability, realizing efficient, flexible and safe external data sharing and utilization, and overcoming the defect that data security and efficiency are difficult to consider in the prior art.

The application provides a multi-regulatory domain real-time compliance decision and data management method for humanoid robots, and relates to the technical field of robot control and data security. The method comprises the following steps: acquiring environment perception, ontology state and target task instruction in real time; identifying the current regulatory domain based on the environment perception data and calling the corresponding regulatory constraint set; calculating the dynamic compliance influence factor according to the ontology state, the task instruction and the regulatory constraint set; generating an executable subtask sequence that conforms to the regulatory constraint set based on the factor to decompose and reconstruct the task instruction; monitoring the interactive data flow in real time during execution, calculating the regulatory domain operation entropy based on the data privacy rules and the dynamic compliance influence factor; judging whether the entropy exceeds the preset safety threshold; if yes, triggering the blocking, desensitization or degradation processing, and outputting the final control instruction. The application realizes multi-regulatory domain real-time compliance decision and dynamic data management, avoids cross-domain violations, guarantees privacy security, and continuously optimizes the decision accuracy through a self-learning mechanism.

This application discloses a method and system for automated processing of multi-source data. The method includes: collecting raw data from heterogeneous data sources and marking the raw data with privacy levels to obtain marked raw data; matching corresponding privacy rules in a preset privacy rule library according to the privacy level, and standardizing the marked raw data based on the privacy rules to obtain standardized data; responding to triggered business instructions, matching a target template from a preset business template library, and filling the target template with standardized data to generate a current result file; and delivering the current result file to the target business system associated with the business instruction to execute the business operation corresponding to the business instruction. This application can match differentiated processing rules based on data privacy levels to achieve targeted security processing of data with different levels of sensitivity, thereby ensuring automated closed-loop processing of the entire data process and effectively reducing the risk of data leakage.

The invention provides a multi-regulation domain real-time compliance decision and data management and control method for a humanoid robot, and relates to the technical field of robot control and data security. The method comprises the steps of obtaining environment perception, an ontology state and a target task instruction in real time; identifying a current regulation domain based on the environmental perception data and calling a corresponding regulation constraint set; calculating a dynamic compliance influence factor according to the ontology state, the task instruction and the regulation constraint set; decomposing and reconstructing the task instruction based on the factor to generate an executable subtask sequence conforming to a regulation constraint set; monitoring interaction data flow in real time during execution, and calculating a regulation domain operation entropy based on a data privacy rule and a dynamic compliance influence factor; judging whether the entropy exceeds a preset safety threshold value or not; if yes, blocking, desensitization or degradation processing is triggered, and a final control instruction is output. According to the method, real-time compliance decision making and dynamic data management and control of multiple regulation domains are realized, cross-domain violation is avoided, privacy security is guaranteed, and decision making precision is continuously optimized through a self-learning mechanism.