29 results about "Right to privacy" patented technology

The invention provides a private weight self-adaptive heterogeneous data federated cooperative training method and system in the technical field of federated learning and privacy computing, and the method comprises the steps: S1, enabling each client to carry out the differential privacy operation on a local data set based on a private weight, and obtaining a desensitized data set, encoding the desensitized data set through a heterogeneous data encoding model; s2, performing semantic alignment on each coding vector through a contrast learning model to obtain an aligned vector set; s3, training a local model through the alignment vector set, generating a local gradient, extracting local model parameters, and uploading the privacy weight, the local gradient and local difference parameters to a server; and S4, the server trains the global model based on the local difference parameter and the global gradient, extracts the global model parameter and issues the global model parameter to each client for training. The method has the advantages that the compatibility, the flexibility and the efficiency of heterogeneous data federation cooperative training are greatly improved.

The invention discloses an image depth compressed sensing method and system for multilevel privacy protection, and relates to the technical field of image processing and information security, and the method comprises the steps: partitioning an image and a privacy mask to obtain a plurality of image blocks and a plurality of corresponding mask blocks; calculating the privacy weight of the image block based on the mask block, and dynamically allocating the sampling rate of the image block based on the privacy weight; judging a privacy block from the plurality of image blocks according to the privacy weight, and applying reversible encryption disturbance to the privacy block based on the key to obtain a disturbed privacy block; performing compressed sampling on the non-privacy block and the disturbed privacy block according to the sampling rate allocated for each image block to obtain an observation value; and inputting the observation value into a pre-trained double-branch reconstruction network, performing reconstruction through a first branch based on the observation value to obtain a privacy protection image, performing reconstruction through a second branch based on the observation value in combination with a key of a completely authorized user to obtain a high-fidelity image, and realizing image privacy protection and high-quality reconstruction under a deep compressed sensing framework.

This application provides a method, apparatus, electronic device, and computer-readable storage medium for privacy protection during the charging process. The method includes: acquiring environmental information during the charging process based on a charging device, and identifying the environmental type during the charging process based on the environmental information; determining the charging type of the charging device based on monitored power status information; performing risk identification processing on the privacy permissions corresponding to the charging type to obtain the risk type during the charging process; thus, by obtaining multi-dimensional information during the charging process, namely environmental type, charging type, and risk type, a comprehensive judgment is made to perform risk control processing on the charging process. This application can improve the accuracy of risk control processing and ensure privacy security during the charging process, such as data security and property security.

A system for processing privacy permissions for consumers utilizing vendor applications allows for recording, storing, and retrieving consent transactions performed by the users (data subjects) in data schemas. The system uses a number of hash-generated IDs, such that when a request is received to retrieve subject data, an organization ID (associated with the vendor or application) and identifying value (associated with the subject) are hashed to create a subject ID. The subject ID, organization ID, and a schema ID for the schema associated with the subject are hashed to create a subject data ID, which is then used to retrieve consent transactions and permissions associated with the subject.

This application provides a method and system for detecting privacy permissions in game publishing access, including: extracting a permission declaration list and decompiled bytecode from the game publishing code product, identifying the degree of code obfuscation and hardening, and obtaining a symbol integrity retention identifier; determining the target tracing mode based on the symbol integrity retention identifier, the target tracing mode including a full-link tracing mode and a shallow tracing mode; using a bytecode tracing unit to traverse the decompiled bytecode according to the target tracing mode, locating the actual call location of each permission item, and obtaining a permission call mapping table; performing a difference operation on the permission declaration list and the permission call mapping table, filtering out permission items that are declared but not called, and obtaining a preliminary set of unused permissions; identifying the target tracing mode of the preliminary set of unused permissions, wherein the full-link tracing mode corresponds to high confidence and the shallow tracing mode corresponds to low confidence, and determining the confidence level of the result.

A system for processing privacy permissions for consumers utilizing vendor applications allows for recording, storing, and retrieving consent transactions performed by the users (data subjects) in data schemas. The system uses a number of hash-generated IDs, such that when a request is received to retrieve subject data, an organization ID (associated with the vendor or application) and identifying value (associated with the subject) are hashed to create a subject ID. The subject ID, organization ID, and a schema ID for the schema associated with the subject are hashed to create a subject data ID, which is then used to retrieve consent transactions and permissions associated with the subject.

The embodiment of the invention discloses an electronic data processing method, a security electronic terminal thereof, a target electronic terminal and a storage medium, the method is applied to the security electronic terminal, and the method comprises the steps that a matching request signal is sent to the outside, and the matching request signal carries a handshake protocol; according to the handshake protocol, searching a target electronic terminal which is also preset with the handshake protocol; and determining the target electronic terminal according to a matching success signal sent by the target electronic terminal, so that the target electronic terminal performs image distortion processing on an image or a video shot by the target electronic terminal. The target electronic terminal carries out image distortion processing on images or videos shot by the target electronic terminal, so that the privacy right and portrait right of a person holding the security electronic terminal are protected and prevented from being abused by others, and the personal safety of the person can be protected.

The invention belongs to the technical field of authority management, and particularly discloses a privacy authority dynamic management and control method and system for a mobile equipment application program, and the method comprises the steps: collecting biological characteristic information of a user and verification password information, carrying out the deep fusion, obtaining a user digital signature, carrying out the verification matching of the user digital signature and a verification digital signature, and obtaining a privacy authority dynamic management and control result. According to the method, the configuration permission level is determined according to the use compliance data of the user, then the configuration permission level is dynamically adjusted based on the use compliance data of the user to obtain the dynamic permission level, and finally the permission of the user for subsequently operating the target application program is managed and controlled according to the dynamic permission level, so that finer and safer application program privacy permission management and control can be realized. Through two-factor fusion authentication and dynamic permission adjustment, the problems of insufficient static authorization and permission abuse in the prior art can be effectively solved, fine-grained permission control in the application program of the mobile equipment is realized, and the method has good applicability and popularization prospects.

A system and method for dynamically optimizing online privacy recommendations for entity users. Certain aspects of the present disclosure provide for methods and systems for optimizing an entity privacy rights recommendation in online transactions. In certain embodiments, an entity user creates an account within an end user application comprising a graphical user interface configured to display one or more privacy rights education prompt and an entity user privacy score. The entity user is assigned a unique alpha-numeric identifier for the entity user within the entity user account. The end user application is configured to match the entity user to one or more online category good or service vendor according to the unique alpha-numeric identifier and provide an entity privacy rights recommendation comprising the one or more online category good or service vendor matched to the entity user.

The application discloses a kind of low-voltage AC-DC distribution network planning method and device, for taking into account the privacy right of each market participant and the benefit of each planning subject, so as to improve the economy of low-voltage AC-DC distribution network planning scheme, improve the benefit of each planning subject.

Example embodiments of the present disclosure are directed to an optimal error- privacy trade-off in information processing system. A method comprises obtaining transmission property information of a link between the first apparatus and a second apparatus based on a measurement metric on the link; and obtaining a result associated with a channel coding to a data set used for transmitting to the second apparatus on the link, based on the transmission property information.

The invention relates to the technical field of information protection, in particular to a sensitive information-oriented adaptive feature retention analysis method, which comprises the following steps of: constructing a privacy risk-information utility dual evaluation model comprising a privacy risk analysis unit and an information utility evaluation unit, evaluating sensitive information, and generating a dual evaluation result matrix; based on the dual evaluation result matrix, analyzing an interaction relationship of different feature retention strategies during combined use through a strategy compatibility analysis model to obtain a strategy compatibility matrix; according to the double evaluation result matrix and the strategy compatibility matrix, a plurality of candidate feature retention strategy combination schemes are generated through a hierarchical combination search model, conflict detection is carried out, and a conflict-free optimal strategy combination is generated; and evaluating the influence of the optimal strategy combination on information availability and privacy protection through a performance-privacy balancing mechanism, determining an optimal feature retention scheme within a preset time, and performing feature retention on the sensitive information to obtain feature retention information.

The invention discloses an object searching method and device, and the method achieves the targeted release and privacy isolation of object searching information through the classification of public information and encrypted information of the object searching information, avoids the leakage of the privacy information of a searched object, guarantees the privacy right of the searched object, and improves the privacy of the searched object. The infringement risk of the first user is reduced; an information verification mechanism ensures that the encrypted information can only be accessed by the second user meeting the condition, so that the exclusive right and the security of information access are guaranteed; meanwhile, the publication of the public information on the preset platform can attract more attention to assist in searching the searched object, the exclusive access of the encrypted information ensures the privacy of the core information, and finally, the accuracy and the efficiency of searching the searched object are improved on the premise of not leaking the privacy, so that the user experience is improved. And the dual requirements of the first user for spreading the object searching information and efficiently searching the searched object on the basis of privacy protection are met.

The application discloses an optimal error privacy trade-off in information processing system. A method comprises: obtaining transmission property information 2035 of a link between the first apparatu

This invention relates to the field of data protection technology, specifically to a method and system for secure transmission of elderly health privacy data. It solves the technical problem that applying a uniform protection strategy to all health data makes it difficult to achieve an ideal balance between ensuring privacy and maintaining data availability. The method includes: acquiring multiple health monitoring parameters of the target object during the data transmission period; determining the transmission impact degree of the target health monitoring parameters based on the data volume variation characteristics of the target health monitoring parameters during the data transmission period and the privacy weight coefficient of the target health monitoring parameters; determining the noise addition intensity based on the difference between the transmission impact degree and the reference impact degree; and performing noise processing on the data to be transmitted of the target health monitoring parameters based on the noise addition intensity. This invention is used in scenarios involving secure transmission of elderly health privacy data.

The application claims a task offloading method for privacy quantification in edge computing, aiming to optimize privacy protection and resource scheduling in the task offloading process. The strategy is implemented through the following steps: first, define the associated privacy weight according to the security requirements of subtasks; then, establish a directed acyclic graph (DAG) based on the dependency relationship between subtasks; next, establish a computing model for task offloading, including transmission delay, processing delay, energy consumption, etc.; calculate the priority of subtasks and processors to determine the order of task execution; finally, based on the idea of greed, schedule each subtask and assign it to the processor with the highest priority for processing. This strategy considers the balance between privacy protection and task scheduling, effectively reducing the risk of privacy leakage and optimizing the utilization of computing resources. It is suitable for computing task offloading scenarios with complex task dependency relationships and privacy protection requirements.

A privacy-compliant modular AI gateway system (100) implemented as a hardware gateway device or as a server-based processing unit within an enterprise network and configured to connect to one or more enterprise resource systems (110), comprising: an input interface (120) including a data ingestion parser (122) configured to receive and parse enterprise data from one or more enterprise resource systems (110), including legacy enterprise resource planning (ERP) platforms (112), enterprise databases (114), or enterprise applications (116); a processing gateway module (130) functionally connected to the input interface (120) and configured to act as an intermediary communication layer between the enterprise resource systems (110) and an external, cloud-based artificial intelligence platform (150);a module (132) for masking personally identifiable information (PII), which forms part of the processing gateway module (130) and comprises: a detection engine (132a) configured to identify sensitive data fields within the received enterprise data, wherein the detection engine (132a) comprises a pattern recognition unit (132a-1), a rule engine (132a-2) and a named entity recognition model (132a-3); a classification unit (132b) configured to categorize identified sensitive data according to sensitivity levels and data categories; and a masking engine (132c) configured to apply safeguards to the classified fields containing sensitive data, comprising a tokenization unit (132c-1), an anonymization unit (132c-2), an encryption unit (132c-3) and a redaction unit (132c-4);a data preprocessing and filtering module (134) designed to clean, structure, and filter enterprise data, comprising a schema normalization unit (134a), a data validation unit (134b), and a content filtering unit (134c); a policy validation module (136) configured to apply predefined regulatory and policy-related restrictions to the processed data; an access control module (160) comprising an authentication unit (162) and an authorization unit (164) configured to authenticate and authorize incoming data requests prior to processing by the PII masking module (132);and a secure communication interface (140) comprising an encryption module (142) and an API gateway (144) configured to transmit protected corporate data to the cloud-based artificial intelligence platform (150) via secure network protocols;wherein the processing gateway module (130) is configured to receive parsed enterprise data from the input interface (120), to authenticate and authorize incoming data requests via the access control module (160), to identify and classify sensitive data fields via the PII masking module (132), to apply tokenization, anonymization, encryption or redaction to the sensitive data fields, to normalize and validate the cleaned data via the data preprocessing and filtering module (134), to enforce predefined policy restrictions via the policy validation module (136), and to output protected enterprise data to the cloud-based artificial intelligence platform (150) via the secure communication interface (140).

Example embodiments of the present disclosure are directed to an optimal error- privacy trade-off in information processing system. A method comprises obtaining transmission property information of a link between the first apparatus and a second apparatus based on a measurement metric one the link; obtaining a first privacy parameter based on the transmission property information; and obtaining a result associated with a channel coding to a data set used for transmitting to the second apparatus on the link, based on at least one of: the first privacy parameter, a second privacy parameter required by the data set, the measurement metric, or the transmission property information.

The application provides a privacy weight adaptive heterogeneous data federal collaborative training method and system in the technical field of federal learning and privacy calculation, and the method comprises the following steps: S1, each client performs a differential privacy operation on a local data set based on a privacy weight to obtain a desensitized data set, and encodes the desensitized data set through a heterogeneous data encoding model; S2, through a contrast learning model, semantic alignment is performed on each encoding vector to obtain an aligned vector set; S3, the local model is trained through the aligned vector set to generate a local gradient, local model parameters are extracted, and the privacy weight, the local gradient and a local difference parameter are uploaded to a server; and S4, the server trains a global model based on the local difference parameter and a global gradient, extracts global model parameters and sends the global model parameters to each client for training. The application has the advantages that the compatibility, flexibility and efficiency of the heterogeneous data federal collaborative training are greatly improved.

The invention discloses a big data privacy protection system in a cloud environment, which relates to the technical field of data access control and comprises a multi-source privacy feature data acquisition module, a privacy data preprocessing module, a privacy data comprehensive analysis module and a privacy protection strategy dynamic execution module. The privacy data comprehensive analysis module comprises a sensitive weight unit, a privacy risk unit and an access decision unit, and the privacy protection strategy dynamic execution module executes privacy protection measures based on data output by the privacy data comprehensive analysis module. Multi-dimensional parameters such as ethical sensitivity levels are integrated through the sensitive weight unit to quantify sensitive field privacy weights, the privacy risk unit combines access popularity and the like to assess risk scores of data blocks, the access decision unit integrates the risk scores, user credibility levels and the like to output authorization decision values, parameters of all the units are coordinated, and the security of the data blocks is improved. And accurate and dynamic field-level, data block-level and access-level basis is provided for data privacy protection and reasonable utilization.

The invention discloses a medical payment information processing platform and method based on a block chain. According to the invention, through deep fusion of the dynamic privacy authority management module and the block chain technology, refined management and control and whole-course traceability of medical data access are realized. An authority strategy execution engine in the dynamic privacy authority management module is linked with the intelligent contract management module, and the data access authority can be automatically adjusted according to the authorization range of the patient, for example, only doctors in specific departments are allowed to check related medical record fragments during diagnosis and treatment, and exposure of full data is avoided. A chain type storage log generated by the authority audit log sub-module is combined with the tampering-free characteristic of the block chain data storage module, it is ensured that each time of data access and authority change operation are completely recorded and cannot be deleted, a supervision mechanism can directly trace an operation source through an audit query interface, the control right of a patient for privacy data is met, and the operation efficiency is improved. And medical data supervision requirements are met.

The application provides a vehicle privacy data processing method and device, electronic equipment and storage medium, and relates to the technical field of vehicle assistance.The method comprises the following steps: dividing the complete function corresponding to the vehicle-mounted application of a vehicle into at least two sub-functions; setting the privacy permission state corresponding to each sub-function according to a preset constraint condition; wherein the privacy permission state at least comprises an authorized state; determining the target sub-function whose privacy permission state is the authorized state; and acquiring the privacy data required to realize the target sub-function.The application realizes the splitting of the function of the vehicle-mounted application by dividing the complete function of the vehicle-mounted application into at least two sub-functions.The privacy permission state corresponding to the sub-function can be set according to the constraint condition, so that the regulatory requirements of privacy data in different regions can be met.The privacy data is collected according to the privacy permission state, which avoids the problem of user privacy information leakage caused by excessive information collection and protects the privacy of the user.

This application provides a data privacy measurement method for intelligent connected vehicles, comprising: calculating privacy attribute weights using the analytic hierarchy process (AHP) and adjusting them based on user privacy preferences to generate personalized privacy weights; generating personalized privacy risks using weighted information entropy and periodically updating them according to a sliding time window mechanism; calculating the probability distribution of privacy leakage in time and space dimensions using gamma distribution and generating spatiotemporal privacy risks, which are also updated using a sliding time window mechanism; fusing personalized privacy risks and spatiotemporal privacy risks using a weighted average to generate a comprehensive privacy risk value, and verifying the accuracy of the measurement results using privacy assessment parameters. This application can effectively protect the privacy and security of intelligent connected vehicles, adaptively adjust privacy protection strategies according to user needs, and ensure the privacy and security of intelligent connected vehicles in different environments.

The invention discloses a privacy authority management method, electronic equipment and a computer readable storage medium. The privacy authority management method comprises the steps of collecting multi-modal data corresponding to a target application program or / and background data according to a set frequency; wherein the multi-modal data comprises at least one of a current environment, user behavior data, feature data of a user, a frequency of accessing a target application program or / and background data, and a current time period; the target application program or / and the background is an application program with permission limitation; and if it is determined that an abnormal condition is detected based on the multi-modal data, starting a coping strategy corresponding to the abnormal condition. Through the method, the matching degree between the actual use scene of the user and the application permission demand can be accurately identified, and the privacy security of the user is effectively protected.

A system that includes an adaptive exchange (ADX) platform in an Internet of Everything (IoE) ecosystem is disclosed. The ADX platform addresses the challenges of data trading, integrity, and value creation. The ADX platform establishes a secure data-sharing framework through data carnets, facilitating transparent agreements for data exchange. Moreover, the ADX platform ensures data privacy, putting data control back in the hands of owners, effectively inverting the traditional privacy-power dynamic. The ADX platform performs secure computation and generational data creation, assuring data integrity and long-term value. The system empowers data owners to securely share their data collections and earn recurring revenue, fostering a robust, user-centric IoE data ecosystem. In essence, the ADX platform transforms data trading, making data a driving force for innovation in our connected world.

Example embodiments of the present disclosure are directed to an optimal error privacy trade-off in information processing system. A method comprises obtaining transmission property information 410 of

The present application relates to the field of information security technology, specifically to a strategy self-adaptive regulation and control method based on data feedback analysis. The method includes comparing handshake request flow with historical strategy set, generating initial configuration strategy to configure main processor; extracting hardware monitoring flow to generate computing power state set, when exceeding preset computing power threshold, according to privacy weight value of business data flow, cutting load data area into core encryption block and basic verification block; respectively configuring full encryption operation code and sampling verification operation code to generate bypass verification task, importing bypass trusted execution area to generate security verification result; extracting reverse frequency of change record in main processor, when greater than preset oscillation threshold, generating damping isolation instruction to lock strategy update thread. The present application optimizes throughput and security distribution mechanism of data management in concurrent scenario through overall architecture design of low coupling execution and high cohesion regulation and control.

A method for context-based data privacy can include receiving an electronic file, determining that the electronic file includes a plurality of data variables that contain privacy-sensitive information related to at least one of a plurality of entities, causing presentation of a user interface specifying a plurality of fields of the electronic file on a computing device of a user, receiving a user selection of a subset of the plurality of fields each including one of the plurality of data variables, analyzing the electronic file using one or more rules to generate context data indicating a privacy privilege level for each field of the subset of fields, determining a de-identification process for each data variable in a respective field of the subset of fields based on one or more rules of the contextual privacy system and the privacy privilege level for each field of the subset of fields, and causing one or more data variables from the subset of fields to be modified using one or more respective de-identification processes.

The application discloses a backdoor attack resistant federated learning method, first, a few benign model updates with high confidence are selected through clustering-based voting, then the selected model updates are regarded as benign patterns of model updates, and a variational autoencoder-based anomaly detection method is used to gradually select more benign model updates from the remaining candidate model updates, so that the size of the selected benign model update group is continuously expanded. The application does not depend on differential privacy, weight clipping and learning rate adjustment, only makes slight changes to the original federated learning protocol, has little influence on the accuracy of the global model, and is convenient for integration with the existing federated learning system. Compared with the existing federated learning methods resisting backdoor attacks, the application has stronger adaptability.