135 results about "User privacy" patented technology

The application provides a user positioning method and device for low-orbit satellite communication and satellite network equipment, relates to the technical field of satellite communication, and the device comprises a receiving unit configured to receive a transmission delay and a Doppler frequency shift reported by a terminal device; a first processing unit configured to control the satellite network equipment to perform the following first operation: calculating a first included angle from the terminal device to a subsatellite point via a satellite according to the transmission delay and an orbital height of the satellite; calculating a second included angle from the subsatellite point to the terminal device in a satellite moving direction via the subsatellite point from a satellite overhead angle according to the first included angle, the Doppler frequency shift, a carrier frequency and a satellite moving speed; and determining position information of the terminal device according to the first included angle and the second included angle. The application can automatically estimate the position information of the terminal device without the terminal device reporting the position information, ensure the service continuity of a communication architecture depending on the terminal device information, and protect the user privacy and safety.

The application discloses a collaborative filtering recommendation method and system based on adaptive noise adding privacy protection, and the method comprises the following steps: suspected abnormal users are screened out by using a DBSCAN algorithm, and true abnormal users are determined by using a box chart, so that abnormal user data in a user data set is screened out; the similarity between each user is calculated, different sizes of noise are added according to the similarity value, and a user similarity noise matrix is constructed; an initial centroid is selected according to the user similarity noise matrix by using a k-means algorithm, and iterative updating is performed, so that user data clustering is realized; a recommendation list is obtained according to a neighbor set of a target user; and items are recommended to the target user according to the scores of the items in the recommendation list. Through the technical scheme of the application, the accuracy of the recommendation result is improved, the user privacy is protected, the problem that the clustering centroid deviates greatly is avoided, and the problem that noise is continuously accumulated in the iteration process to cause the final recommendation result to be inaccurate is avoided to a certain extent.

The application relates to the field of big data, in particular to a model training method and a user intention prediction method. The method is applied to a cloud side device in a data processing system, the data processing system further comprises at least one end side device, and the method comprises the following steps: acquiring encrypted data reported by the end side device; wherein the encrypted data is data obtained by encrypting historical behavior data of a user by the end side device; generating a first event according to the encrypted data; wherein the first event is a general event which does not comprise user information; and training a first model according to the first event, wherein the first model is a general model used for predicting user intention. Through the above method, the cloud side device realizes the training of the prediction model of the user intention under the premise that specific user information cannot be obtained, thereby facilitating the protection of user privacy.

This invention discloses a fall detection method, apparatus, device, and medium. The method includes: determining target noise point detection information corresponding to the target radar detection information of a target person based on personnel radar detection information detected by millimeter-wave radar and noise point detection information detected by an acoustic detection device; determining the detection mode of the target person based on the target radar detection information, and determining target detection information from the target radar detection information and target noise point detection information based on the detection mode; wherein the detection mode includes an obstruction mode, a stationary mode, and a motion mode; and detecting the fall state of the target person based on the target detection information. This invention uses a combination of millimeter-wave radar and acoustic detection for fall detection, enabling continuous fall state detection even when the target person is obstructed by objects indoors, improving the accuracy and efficiency of fall detection; and since both millimeter waves and acoustic waves are invisible waves, user privacy can be effectively protected.

This invention provides an attribute-based searchable encryption method based on SM9 to resist keyword guessing attacks. It aims to address the security flaws of existing solutions, which are vulnerable to server-side keyword guessing attacks during encrypted retrieval. By cryptographically binding and randomizing user identity identifiers, attribute sets, and keywords, a complete encryption, retrieval, and verification mechanism is constructed. Its core lies in reconstructing the security trapdoor generation and verification process using the SM9 algorithm, preventing the server from offline enumerating and guessing keywords without proper attribute permission verification. This achieves secure, controllable, and efficient encrypted retrieval while ensuring data confidentiality and user privacy, meeting the urgent needs of smart grids for secure and autonomously controllable data sharing technologies.

The application provides a data processing method and device, a computer program product and a readable storage medium, and relates to the technical field of data processing. A data processing device obtains first application data of a first terminal, and the first application data is used to indicate the type of an application program possessed by the first terminal. The data processing device processes the first application data of the first terminal by using a first model, so that a first user type corresponding to the first terminal can be obtained. The data processing device can send first push information matched with the first user type to a user of the first terminal based on the obtained first user type corresponding to the first terminal. The data processing device predicts the first user type of the user of the first terminal according to the first application data of the first terminal on the premise of protecting the privacy of the user of the terminal, pushes information interested by the user of the first terminal to the user, realizes accurate push of information, and improves the user experience.

Embodiments of this disclosure provide a control method, apparatus, device, computer program product, and computer-readable storage medium. The method determines contextual information, including location information, of at least one user based on sound data within a space, and controls an audio-visual system to emit directional sound and light signals towards the location of at least one user based on this contextual information. This provides targeted and personalized audio-visual signals to users sharing the same space, ensuring that different users do not interfere with each other and greatly improving the user experience. Furthermore, by determining contextual information including location information based on sound information, user privacy can be significantly protected from disclosure.

This invention discloses a post-quantum secure linkable ring signature method and system resistant to internal attacks, comprising: a first service device generating public parameters; each user device generating its own public-private key pair using the public parameters and sending its public key to the first service device for registration; the first service device verifying all received identity information and forming a public key ring from the public keys of all verified user devices and making it public; when any user device needs to send a message to a second service device, it generates a ring signature containing a linkable tag based on its own private key, the message, and the public key ring, and sends the ring signature and the message to the second service device; the second service device performing security verification on each ring signature and, after successful verification, verifying whether different ring signatures belong to the same user device based on the linkable tag. This invention can protect user privacy in anonymous scenarios, enable multiple signatures from the same user, and resist attacks from within.

The application relates to a personalized privacy risk dynamic measurement method based on a deep neural network, and specifically comprises the following steps: S1, collecting personalized privacy demands of a user, and establishing a personalized user privacy demand vector; S2, according to the personalized user privacy demand vector, extracting a feature matrix in a user picture by using a convolutional neural network, calculating a privacy feature vector from the feature matrix by using the convolutional neural network, multiplying the privacy feature vector with the personalized user privacy demand vector, obtaining a personalized privacy feature vector of the user in the picture, and identifying sensitive privacy information in the picture; and S3, predicting a leakage risk of the personalized privacy feature vector. The application is designed based on a deep neural network, solves the problem of privacy risk assessment from the perspective of user shared privacy image historical behavior characteristics, measures the risk size of user privacy information leakage, reduces the user privacy information leakage risk from the source, and enhances the user privacy consciousness.

The application provides an emotional smart home central control method based on multi-chip cooperation and MCP protocol, and relates to the technical field of smart home control. The method comprises the following steps: collecting and preprocessing user multi-modal data through a multi-heterogeneous perception edge node, encapsulating the data into a standardized data frame containing semantics and space-time attributes through an MCP protocol, and transmitting the data frame to a decision hub node. The decision hub node fuses data to construct a global dynamic emotion topology map, triggers a multi-chip distributed cooperative reasoning mechanism, dynamically schedules resources in combination with system load to generate an emotional control strategy. After the strategy is distributed to an execution device, the edge node continuously monitors feedback data, the decision hub node calculates a deviation value and corrects reasoning parameters through reinforcement learning, and a closed-loop optimization loop is formed. The application improves emotion recognition accuracy and strategy adaptability, protects user privacy, and enhances the humanization and intelligence level of smart home interaction.

The application discloses a processing method, device, equipment, medium and product of device location information. The method comprises the following steps: a UICC of a terminal device receives a first request from a service platform, the first request carrying a first identifier indicating a requester; based on the first identifier and set authorization information, it is determined whether the requester is authorized; if it is determined that the requester is authorized, the location information of the terminal device is sent to the service platform. In this way, based on the interaction between the UICC of the terminal device and the service platform, the sharing of the location information of the terminal device can be realized, and the universality requirement is met. In addition, through the authorization authentication of the requester, the UICC sends the location information of the terminal device to the service platform only after it is determined that the requester is authorized, and then the sharing of the location information can be realized on the basis of giving consideration to the user privacy protection, and the universality and security requirements of the sharing of the location information of the terminal device are met.

This application pertains to the technical field of enterprise data analysis and provides a method and system for constructing a risk prevention and control system based on enterprise digital transformation. The method involves first acquiring multiple access request information and access permission information, then generating authentication result information based on this. If the total number of authentication failures exceeds a conventional threshold, risk event information is generated. This application can promptly detect abnormal behavior during monitoring periods, such as a large number of users attempting unauthorized access to the power supply bureau's core system data. It accurately identifies potential risk events such as privilege abuse, brute-force attacks, internal personnel violations, or external penetration attacks. It provides real-time alerts and decision support for security management personnel, facilitating rapid deployment of countermeasures and effectively preventing the leakage of sensitive electricity consumption information, power grid operating parameters, and user privacy data. This significantly enhances the reliability and proactive defense capabilities of the power supply bureau's data security risk prevention and control system.

With the rapid development of technologies such as the Internet of Things (IoT), smart devices, the Industrial Internet, and the Internet of Vehicles (IoV), various systems collect, process, and store massive amounts of data during operation, including sensitive information such as process parameters of industrial equipment, robot trajectories, location information of vehicle systems, indoor images of smart homes, and trade secrets of enterprise office systems. If this private information is not properly protected, it may lead to serious consequences such as the leakage of trade secrets, infringement of user privacy, and legal compliance risks. Existing technologies suffer from insufficient proactive identification capabilities, simplistic protection strategies, lack of adaptive learning, and disconnected auditing. This application provides a privacy data management method, system, and computer-readable storage medium, aiming to achieve proactive identification, hierarchical protection, adaptive optimization, and end-to-end auditing of privacy information in various types of data. It can be widely applied to various data processing scenarios such as industry, vehicles, homes, and enterprises.

This invention relates to a self-learning method and system for home environment regulation based on multimodal feedback and scene awareness. The method collects the user's physiological characteristics and body movement signals through non-contact sensing devices to identify the user's current activity scene. The system integrates the user's explicit intervention operations with implicit comfort feedback based on physiological stability, dynamically assigning fusion weights for explicit and implicit feedback according to the activity scene to generate target feedback labels. An online incremental learning algorithm is used to update the local environmental control model, and a privacy-preserving model aggregation is performed in the cloud through a federated learning mechanism. This invention solves the problems of traditional home control relying on single commands and lacking physiological feedback mechanisms, achieving intelligent closed-loop control that balances user privacy and personalized comfort.

The application discloses a kind of dynamic food nutrition loss and gain grade evaluation system and method based on food, food material (including herbal plant) ingredient content level and individual health data.System acquires food ingredient data (such as energy, protein, fat, cellulose, potassium, sodium, magnesium, additive, etc.) and individual medical index (such as blood sugar, blood pressure, blood fat, uric acid, height and weight, allergy history, etc.) data, combined with eu nutrition score standard and China's general coefficient, then dynamically adjusts coefficient weight according to individual health condition (such as high blood pressure user adjusts high iron sodium related coefficient), finally generates general health grade and personalized recommendation grade.System presents results through mobile terminal or PC terminal App, and uses encryption technology to protect user privacy.The application solves the problem of lack of individualization in existing evaluation, and provides accurate dietary health guidance for users.

A privacy protection method and system based on a blockchain anti-federated learning gradient attack are related to the technical field of data privacy protection.The technical points of the present application include: when the participant completes the training and uploads the gradient data, the smart contract automatically adds noise values related to the gradient hash value, and the gradient after adding the noise is stored in the blockchain, so the user data cannot be recovered directly through the gradient leakage method; when the center server aggregates the data, the participant calls the smart contract with the hash value of the gradient data as a parameter, the smart contract verifies the uploaded gradient data and then performs the next operation; the smart contract recalculates the noise value and randomly divides it into several parts, and saves each part in the blockchain; the noise required by the center server when aggregating data and the shared noise value of all participants calculated by the smart contract are directly returned to the noise; and the latest model parameters are finally calculated.The present application effectively solves the problem of user privacy leakage and improves the problem of model precision decline.

The application discloses a method for keeping encrypted frequency domain thumbnail with enhanced availability, which realizes the balance between image privacy and enhanced availability. The privacy means to protect the detail part of the image which may contain user privacy, and the enhanced availability means to record additional information as much as possible while keeping the original image thumbnail to maintain the general outline of the image. In the application, the image owner performs space operation on the original image in the frequency domain, then performs stream encryption on the low bits of AC coefficients in each block and keeps the original DC coefficients, so that the ciphertext image and the original image keep the effect of thumbnail approximation. After obtaining the ciphertext image, the information hider records additional information in the fixed position of each block in the frequency domain, and the thumbnail of the ciphertext image is not greatly affected. The image encryption and information embedding process of the scheme are completely reversible, and the image encryption and additional information hiding steps are separable.

The application discloses a user sensitive information protection method based on a data confusion technology, and comprises the following steps: step S1, generating a sensitive attribute association table based on the association between recommended items and user gender characteristics; step S2, adding confusion ratings to an existing user-item matrix through a sampling strategy according to the sensitive attribute association table obtained in step S1, and constructing a user-item matrix after adding the confusion ratings; step S3, recording the number of confusion ratings added in step S2, applying a removal strategy, and finally generating a confusion matrix after applying the removal strategy; the removal strategy is that the same number of confusion ratings are deleted to maintain the original data size; a user is randomly selected, and when the rating number of the user reaches a set threshold, the items with strong association of the opposite sex are deleted from the rating history of the user. The application can mislead attackers to conduct gender attribute inference, realize user privacy protection, and does not affect the existing personalized recommendation quality of the user.

The embodiment of the present application provides an access control method and an electronic device. In the technical scheme provided by the embodiment of the present application, a first application is called to generate a calling request, or a calling request sent by a first electronic device through calling a first application is received, the calling request is used for requesting a second application to call a target service; whether the calling request is allowed is judged according to a security policy pre-configured by a user, the target service, the first application and the second application; if it is judged that the calling request is not allowed, the calling request is rejected, and prompt information for prompting that the first application is abnormally operated is generated. The embodiment of the present application enables the current mobile OS to effectively find and block the user privacy leakage problem in a distributed system composed of multiple devices.

The application discloses a kind of distributed multi-dimension health management data acquisition intervention system and method, belong to health management technical and intelligent information service technical field.System includes personal data access end, data security processing center, health analysis and management engine, privacy file library and health analysis database.Through generating unified original identification for binding data and deriving anonymous health ID of no inference relationship, identity file and health data are respectively encrypted and stored in physically or logically isolated library, and the association is saved by means of independent encrypted identification mapping library.System uses mixed access control strategy based on role and attribute, so that health management teacher can only access desensitized data based on anonymous ID and carry out intelligent analysis and intervention, while supporting temporary authorized access under strict approval process.The application realizes the complete isolation of identity and health data, supports the safe use of data and personalized health services under the premise of protecting user privacy.

The present application relates to the field of data security sharing, and discloses a multi-keyword fuzzy search data sharing method based on attribute, a computer device and a storage medium; the data sharing method involves five entities of a data owner, a user, a trusted authorization center, a consortium chain and a cloud storage service; the trusted authorization center initializes and registers a policy template to the chain, the data owner uploads a policy commitment and a proof to the chain, encrypts data and an index and then uploads to the cloud, the user generates a trapdoor and a proof, obtains a token through chain verification, and finally retrieves and decrypts data from the cloud safely with the token; the method realizes data confidentiality, fine-grained access control and traceability of the source, guarantees user privacy and policy compliance through zero-knowledge proof and on-chain verification, prevents the cloud server from inferring information through the blind index and token mechanism, realizes separation of search and authorization responsibilities, and balances efficient sharing and strong security.

This application provides an audio cloning method and related equipment based on cloud computing technology to ensure the security of cloned voice and prevent user privacy leaks. The method is applied to a cloud platform, which manages the infrastructure running cloud computing services. The infrastructure includes at least one data center, and each data center includes multiple servers. The method includes: acquiring original audio from a first tenant; encrypting the original audio to obtain encrypted audio; and storing the encrypted audio in the infrastructure. Acquiring a first text from the first tenant. Decrypting the encrypted audio to obtain the original audio. Synthesizing the original audio and the first text to obtain cloned audio, where the sound features of the cloned audio are identical to those of the original audio, and the content of the cloned audio is the content of the first text.

A communication method and apparatus, belonging to the field of communications, are disclosed. The method includes: a first module receiving a first parameter from a first network, the first parameter being a calculation parameter of a first security mechanism; the first module obtaining a second hidden identity identifier based on the first parameter, the second hidden identity identifier being a hidden identity identifier obtained by processing plaintext identity information according to the first security mechanism and the first parameter. A terminal-side device includes a first module supporting the first security mechanism and a second module not supporting the first security mechanism. The terminal-side device can first use the hidden identity identifier calculated by the second security mechanism to access the network, thereby using an anonymized identity identifier during network access to protect user privacy. The network side can issue calculation parameters of a first protection mechanism with higher security strength, enabling the terminal-side device to provide a higher level of security for user identity privacy protection during subsequent access processes.

This invention discloses a privacy-enhanced local vectorized knowledge base reasoning system and method. It obtains user information to be protected for privacy purposes and performs semantic decomposition on the user information based on the user terminal to obtain personal identification information and question information. The personal identification information is stripped, and the question information is abstracted into a general intent tag. Homomorphic encryption technology is used to retrieve knowledge fragments matching the general intent tag, and the knowledge fragments are anonymized for user privacy. Reasoning instructions are generated based on the anonymized knowledge fragments and the general intent tag. The reasoning instructions are assigned to the target reasoning model for reasoning processing according to preset rules. Temporary data of the target reasoning model is cleared. The reasoning results are anonymized for privacy, and the behavior logs of the target reasoning model are audited for privacy. This achieves privacy-enhanced local vectorized reasoning that is data-usable but not visible, fully controllable and auditable, and compliant with privacy regulations.

A sensing communication method and apparatus are applied to the field of communication technologies. This application may be applied to a wireless local area network system supporting a next-generation Wi-Fi protocol (for example, 802.11be, Wi-Fi 7, or EHT) of IEEE 802.11ax, a next-generation Wi-Fi protocol (for example, Wi-Fi 8 or UHR) of IEEE 802.11be, Wi-Fi AI, a millimeter wave (mmWave), an ultra-wideband (UWB), or sensing (sensing). For example, after generating a PPDU based on Q time-variant function values, a first communication apparatus sends the PPDU. After receiving the PPDU, a second communication apparatus may parse the PPDU based on the Q time-variant function values agreed on by the second communication apparatus and the first communication apparatus. According to the method provided in embodiments of this application, information transmission security is improved, and user privacy is effectively preserved.

This invention relates to a localized differential privacy recommendation method and system that balances algorithmic fairness, belonging to the fields of computer recommendation systems and information security technology. The method first divides the dataset into three groups—active, moderate, and inactive—based on user activity. The server initializes and pre-trains the item latent factor matrix, saving the latent factor matrices for each group. Gradient updates and dynamic gradient clipping are performed on each group, adaptively adding noise based on a clipping threshold. In each iteration, the gradient clipping threshold and noise scale are updated. Each group uploads the perturbed item gradients to the server for secure aggregation. Finally, the recommendation server uses the updated item latent factor matrix and distributes it to the local group for further training. After iteration, users generate a top-K recommendation list through local prediction. This invention effectively protects user privacy in scenarios where the server is untrusted, significantly alleviates the performance differences in recommendations between user groups with different activity levels, and achieves a balance between privacy protection and algorithmic fairness.

This application relates to the field of wireless communication technology, and more particularly to a communication method and communication device. In an embodiment of this application, a first communication device determines a first data processing mechanism and instructs the first data processing mechanism to a second communication device via first information. The first data processing mechanism is used to perform privacy protection processing on data from computing services. This application avoids exposing users' private data and protects user privacy and security.

The aim is to allow video confirmation at the control center as needed, even when security is deactivated, while respecting user privacy. [Solution] The security system 100 includes an imaging device 10 that captures images of a predetermined security area S, a security device 30 that acquires images from the imaging device 10, a security terminal 50 that requests the security device 30 to display the images and displays the images when the request is approved, and a user terminal 60 that receives an image display signal indicating that the security terminal 50 has displayed the images. When the security device 30 approves the security terminal's request to display the images, it transmits the images to the security terminal 50 and also transmits an image display signal to the user terminal 60.

This invention discloses a multi-dimensional privacy information perception and collection method. It constructs a formal description model of multi-dimensional privacy information, characterizing privacy information from multiple perspectives, including its composition, attributes, permissions, and control. Based on active learning and transfer learning algorithms, it builds a metadata intelligent perception, identification, and labeling method adaptable to various application scenarios and privacy protection strategies. This patent's advantages in adapting to multiple scenarios and information types allow it to adapt to the impact of changing application scenarios on privacy properties, reduce the concealment of privacy information caused by multiple information types, and improve the accuracy of privacy information perception. It focuses on perceiving multiple types of privacy information, comprehensively perceiving different privacy types such as text, images, and sound. Compared to existing single-type privacy perception methods, it is more beneficial for subsequent privacy strategy formulation and privacy control implementation, improving user privacy security. It has strong privacy perception capabilities, can process different types of data in parallel, and offers accurate privacy positioning and fast data processing.