25 results about "Data anonymization" patented technology

This invention discloses a knowledge-based intelligent interpretation system and method for laboratory reports, comprising four sequentially linked modules: a data input module for receiving laboratory data transmitted from the LIS system, the data including patient laboratory indicators and basic patient information, supporting data anonymization, and the basic patient information including at least age, gender, pregnancy status, medical history, and family medical history. This invention effectively reduces patient consultations, allowing patients to understand their reports immediately, reducing anxiety, significantly improving patient satisfaction, avoiding inconsistent interpretations among doctors, enhancing the ability of general practitioners in community hospitals to interpret laboratory reports, and reducing unnecessary duplicate examinations through accurate interpretation.

A data anonymization pipeline system for managing holding and pooling data is disclosed. The data anonymization pipeline system transforms personal data at a source and then stores the transformed data in a safe environment. Furthermore, a re-identification risk assessment is performed before providing access to a user to fetch the de-identified data for secondary purposes.

The application discloses a kind of campus health management system and method based on group benchmark analysis, comprising: data acquisition module, for collecting the health and behavior data of student individual, and implementing data anonymization processing;Data processing and analysis module, including group clustering unit, for clustering the anonymized student individual data into homogenization analysis group according to student group attribute;Benchmark generation unit, for calculating the dynamic statistical benchmark band of one or more health indicators in each analysis group based on historical data within the set time window;Individual comparative analysis unit, for comparing each student individual data with the dynamic statistical benchmark band of corresponding health indicators of its analysis group, and calculating the relative deviation of individual health indicators;Early warning and report generation module, for triggering hierarchical early warning according to individual comparative analysis result, and generating visual health report. It can be widely applied to the field of campus health management technology.

This application relates to the field of data anonymization technology, specifically to a method and system for anonymizing sensitive information in enterprise information databases. The method includes: extracting sensitive fields from the table structure of an enterprise's information database; calculating the first and second correlation degrees between any two sensitive fields to determine their correlation evaluation value; dividing all sensitive fields into multiple sets of related fields, obtaining the anonymization strength of each set, determining the anonymization level of each set, and selecting and executing the corresponding collaborative anonymization strategy. This application can completely block combined inference attack paths and ensure logical consistency of data during the anonymization process, achieving integrated collaboration between security protection and data utility.

A system accesses database tables comprising sensitive data, collecting data elements corresponding to the sensitive data, reduces the data elements to a distinct list of data elements, generates a first script to generate map tables for each data element, wherein each map table comprises a first column to hold original values of the data element and a second column to hold anonymized values for the original values, generates a second script to scan the database tables to collect original values for each data element and populate the original values in a respective map table, generates a third script to anonymize the collected original values for each data element and populate the anonymized values in a respective map table, and generates a fourth script to update the original values using the corresponding anonymized values in the database tables based on the map tables.

The application provides an edge computing-based medical data anonymous distribution system, method, medium and terminal, receives collected initial medical data, processes the initial medical data into corresponding hierarchical anonymous medical data according to a medical data calling request received from a data consumption layer through an edge node, and displays the corresponding hierarchical anonymous medical data to a user. The application overcomes the technical problems of single medical data anonymization processing means, high risk of leakage and lack of correlation between anonymous data in the prior art, can balance privacy compliance and data correlation at the source of multi-source medical data, and is suitable for diversified medical data protection and distribution requirements.

This invention discloses a testing method, apparatus, device, medium, and product for isomorphic migration. The method includes: acquiring raw traffic information recorded by a browser plugin based on user operations on a source environment within a browser webpage, and a first response result from the source environment to the raw traffic information; converting the raw traffic information to obtain target traffic information; sending the target traffic information to a target environment to obtain a second response result from the target environment; and determining the test result of this isomorphic migration based on the first and second response results. This invention can solve the problem of traffic unavailability caused by data anonymization, thus improving testing efficiency.

This invention provides a multi-source fusion-based system and method for calculating peak fatigue levels in runners of up to 10,000 users. The system includes a data acquisition module, a data preprocessing and fusion module, a peak fatigue calculation module, a safety early warning and coordinated intervention module, a data security and privacy protection module, and a backup data acquisition unit. The core functionality involves collecting five-dimensional, multi-source, safety-related data on runners' physiological, exercise, environmental, individual, and subjective factors through the data acquisition module. A simplified version of non-invasive electromyography (EMG) signals is introduced to identify latent muscle fatigue. A dual-layer fusion architecture of "edge + cloud" is adopted, combined with a federated learning model, to achieve deep fusion of multi-source data while protecting runner privacy, constructing a personalized dynamic fatigue threshold model. The system calculates peak fatigue levels based on a real-time safety-oriented fatigue index, implements closed-loop intervention through a four-level graded early warning mechanism linking multiple terminals, and ensures data security through three-link redundant transmission, data anonymization and encryption. The backup acquisition unit ensures full coverage of data from up to 10,000 users.

This invention specifically relates to a financing service management system based on multi-platform data sharing, encompassing the fields of data processing and financing service technology. It includes: a multi-source data acquisition and fusion governance module; an intelligent financing application and processing module; a financial institution collaboration and direct connection module; an intelligent risk control and data-driven decision-making module; and a financing dashboard and decision support module. In this invention, standardized interfaces and a federated learning framework enable secure acquisition and sharing of multi-source data. After data cleaning and standardization, the quality and usability are significantly improved, providing reliable data support for financing services. Simultaneously, through national cryptographic algorithms for data anonymization and compliance control, data acquisition and use are ensured to comply with relevant laws and regulations, reducing compliance risks.

Implementations of the present specification provide an image data processing method, an image data recognition method, a training method for an image recognition model, an image data processing apparatus, an image data recognition apparatus, and a training apparatus for an image recognition model. During image data processing, data anonymization processing is performed on image data based on frequency domain transform to obtain anonymized image data of the image data. The obtained anonymized image data includes a subgraph data set. Each subgraph data in the subgraph data set corresponds to a different frequency. Then, image blending processing is performed on the obtained anonymized image data based on data augmentation, to obtain augmented anonymized image data. In some implementations, graph size alignment processing is performed on each subgraph data in the augmented anonymized image data, so that a size of each subgraph data after the graph size alignment processing is same as a size of the image data in original form.

This invention discloses a method and system for publishing multimodal data in industrial production for artificial intelligence, belonging to the field of industrial intelligence and data processing technology. The method includes: collecting multimodal data and performing hardware-level time synchronization and preprocessing to obtain a synchronized data stream; extracting multimodal features from the synchronized data stream in parallel and using an attention mechanism to fuse networks and generate a unified feature vector; constructing a five-dimensional quality assessment system and intelligently enhancing it; performing structured annotation and version management; adapting and publishing datasets according to AI tasks; implementing multi-level data anonymization and fine-grained access control, embedding invisible digital watermarks, and generating audit logs; and enabling multi-terminal access through a publishing platform. This invention solves the problems of difficult data alignment, poor quality, and low reusability, achieving secure data sharing and providing a high-quality, standardized data infrastructure for industrial AI applications.

An IoT / M2M service layer may be provided with the capability to protect user privacy. This functionality may allow the IoT / M2M service layer to anonymize user data, particularly when user data is shared with third party consumers. A privacy policy service may enable the IoT service layer system to generate anonymization (e.g., privacy) policies based on inputs such as legal obligations, subscriber privacy preferences, and an authorization level of the data consumer. Data anonymization policies may be output from the privacy policy service and may be sent to a data anonymization service, where raw data may be anonymized based on the one or more data anonymization policies. The output from the data anonymization service function may be a privatized (e.g., anonymized) version of data that may prevent the data consumer from discovering one or more identifying characteristics of a user.

A tokenization system receives a request for data anonymization, the request referencing unstructured / semi-structured content containing values of interest. The tokenization system performs a tokenization operation on the unstructured / semi-structured content, generates self-describing tokens for the values of interest, each self-describing token having a preconfigured pattern, an indication of a protection strategy, and a token value, and stores the values of interest in a secure data vault. The tokenization system may receive a request to reveal the self-describing tokens in the unstructured / semi-structured content. In response, the tokenization system searches the anonymized version of the unstructured or semi-structured content for the preconfigured pattern, identifies self-describing tokens, uses the self-describing tokens to retrieve the values of interest from the secure data vault, and produces a detokenized version of the unstructured / semi-structured content containing the values of interest.

This invention discloses a data anonymization system. A data classification module categorizes multi-source data in a database, obtaining structured and unstructured multi-source data. A sensitive data identification module identifies structured sensitive information from the structured multi-source data and uses semantic clustering to identify unstructured sensitive information from the unstructured multi-source data. The unstructured sensitive information is then converted into structured sensitive information through basic parsing. A data privacy module classifies the structured sensitive information according to preset information security levels, obtaining structured sensitive information at each security level. A matching data anonymization method is then used to anonymize the structured sensitive information at each security level, resulting in anonymized multi-source data. This invention achieves one-stop operation for sensitive data management, balancing data security and availability, meeting relevant compliance requirements, effectively reducing the risk of data leakage, and is suitable for sensitive data protection in multiple business scenarios.

This invention discloses a cross-platform AI identification and closed-loop management method and system for anonymized public opinion work orders, belonging to the field of public opinion service management technology. Specifically, it is a cross-platform AI identification and closed-loop management method and system for anonymized public opinion work orders, aiming to improve the efficiency of public opinion work order processing and the level of privacy protection. The method includes: unified access and standardization of work orders across platforms; anonymization and encryption of privacy data, isolated storage and generation of traceability codes; rule-based and feature-based identification and classification; intelligent assignment according to responsibilities and workload, supporting cross-departmental collaboration; real-time monitoring of processing progress, with timeout level reminders and escalation; anonymous feedback of results and collection of satisfaction, with review for unsatisfactory results; closed-loop archiving and process optimization based on data analysis. The system includes cross-platform access, anonymization processing, identification and classification, assignment and collaboration, processing control, feedback collection, archiving optimization modules and a database. The modules work together to achieve secure and efficient closed-loop management of the entire work order process.

The invention relates to a device and method for protecting sensitive personal data held in a public storage, comprising a trusted tokenization system having at least one trusted interface to an instance that may provide, process, possess, and / or retrieve sensitive personal data, and at least one interface to a public storage not containing sensitive personal data, wherein the tokenization system is configured to replace a sensitive personal reference of the data in the public storage with a non-sensitive data element and to store an association between the sensitive personal reference and the non-sensitive data element in a secure environment, wherein the non-sensitive data element is generated in a user-specific manner such that the non-sensitive data element can be processed in an existing infrastructure of a user without adaptation of said infrastructure.

This application discloses a data anonymization method, apparatus, storage medium, and electronic device. Relating to the field of data processing, the method includes: acquiring data to be anonymized; identifying sensitive fields from the data to be anonymized, and determining a target bitmap corresponding to the data to be anonymized based on the sensitive fields, wherein different bits in the target bitmap correspond to different sensitive fields, and the target bitmap represents the sensitive fields contained in the data to be anonymized based on the bit values; determining anonymization rules matching the target bitmap, and anonymizing the data to be anonymized according to the anonymization rules to obtain anonymized data. This application solves the problem of low flexibility in data anonymization in related technologies.

This invention proposes a data anonymization and restoration method, apparatus, and storage medium for a payment system. The method includes: receiving a data anonymization instruction input by a user, the instruction including a data anonymization / restoration identifier and a data usage scenario; retrieving a data object to be anonymized from a database based on the instruction, determining the data type of the data object (structured or unstructured); anonymizing the data object based on its data type, the anonymization / restoration identifier, and the data usage scenario, and sending the anonymized data to the user, wherein the anonymized data includes the anonymization / restoration identifier. To address the shortcomings of static data anonymization in payment systems, this invention proposes a dynamic data anonymization solution based on data type, the anonymization / restoration identifier, and the data usage scenario, thereby improving data security.

A data anonymization service of an application development service is configure to protect sensitive data while providing data context in the reproduction of application events. Upon detection of an execution symptom within a production application, data required to reproduce the symptom is collected as input to an anonymizer to facilitate minimal-trust analysis of the symptom. The data may first be minimized to eliminate data elements not needed to reproduce the symptom, the data elements are identified that are essential to reproduce the symptom are determined to contain sensitive data according to client-provided rules. These identified elements are then transformed to anonymize the sensitive data while preserve reproducibility of the symptom. A modified data set including the transformed data elements may then be provided to an application development service for analysis.

This application discloses a data processing method, apparatus, computer equipment, and storage medium; applied to an IoT device including a data acquisition module. When a first application receives an object data acquisition request from a second application, it authenticates the second application based on the request. The data acquisition module is used entirely by the first application. The request indicates the target business mode corresponding to the object data acquisition. When authentication is successful, the object data corresponding to the request is extracted from the database. The object data is acquired by the first application by calling the data acquisition module. The data anonymization method of the object data is determined according to the target business mode, and the extracted object data is anonymized. Storage address information sent by the second application is received through a secure data channel between the first and second applications. The processed target object data is sent from the first application to the second application based on the storage address information. This improves the efficiency and security of data distribution in IoT devices.

This application provides a data anonymization method, apparatus, and readable storage medium. The method includes: acquiring a dataset to be anonymized; determining an evaluation model based on first task requirements; inputting the dataset to be anonymized into the evaluation model to obtain a first contribution index of each attribute field to the first evaluation result output by the evaluation model; determining the value weight of each attribute field based on its first contribution index; obtaining the field sensitivity of each attribute field; determining the target privacy budget for each attribute field based on its value weight and field sensitivity; and anonymizing each attribute field according to its target privacy budget to obtain an anonymized dataset. This application analyzes the required privacy budget for each attribute field from two dimensions, performs non-uniform allocation of the privacy budget for each attribute field, and performs different anonymization processes on each attribute field to obtain an anonymized dataset that does not significantly disclose important information and reflects its own characteristics.

Streamlining the process of data anonymization. [Solution] The information processing device comprises a data acquisition unit that acquires target data that may contain information to be kept confidential, and a target location estimation unit that estimates the parts of the target data that should be kept confidential using a machine learning-trained language model. This information processing device makes it possible to optimize the entire process related to data confidentiality.

A system for data anonymization includes a memory storing a plurality of database tables comprising sensitive data and a processor operably coupled to the memory. The processor is configured to access the database tables, collect data elements corresponding to the sensitive data, and reduce the collected data elements to a distinct list by removing redundant data elements. The processor further generates one or more scripts configured to generate map tables for each data element, each map table storing original values and corresponding anonymized values, to scan the database tables and populate the map tables with original values, to anonymize the original values and populate the anonymized values in the map tables, and to update the database tables using the anonymized values based on the map tables. Anonymization of a data element in a database table associated with an application is performed according to rules associated with that application.

Embodiments of the present disclosure disclose a user portrait collection and right confirmation method and device, electronic equipment and readable medium. A specific embodiment of the method comprises: collecting a first video frame sequence; collecting a second video frame sequence and article flow data; performing feature dynamic update processing on a preset user portrait feature library based on the first video frame sequence and the second video frame sequence to obtain an updated user portrait feature library; performing subject right confirmation processing on the second video frame sequence based on the updated user portrait feature library to obtain a target user video frame; performing subject portrait identification processing on the target user video frame to obtain subject portrait identification information; performing data anonymization processing on the updated user portrait feature library to obtain security feature information; and creating user portrait information based on the article flow data, the subject portrait identification information and the security feature information, and storing the user portrait information to a database. The embodiment improves the integrity and comprehensiveness of user portrait collection and right confirmation.