79 results about "Information leakage" patented technology

Various techniques are provided to implement information leakage mitigation associated with data communications. In one example, a method includes receiving a bitstream including a plurality of bits. The method further includes, for each bit of the plurality of bits, transitioning between two states of a plurality of states in response to the bit; inverting a differential pair of data signals associated with the bit in response to the transitioning to obtain differentially transitioned data signals; maintaining a third data signal associated with the bit in response to the transitioning; and transmitting each data signal of the differentially transitioned data signals and the third data signal over a respective wire. Related systems and devices are provided.

This invention discloses a secure voice-based intelligent customer service system and interaction method based on a multi-agent architecture. The system includes an ASR (Automatic Speech Recognition) module, multi-layered security barriers, a main retrieval agent, a specialized retrieval agent cluster, a parallel retrieval and result aggregation module, an LLM (Limited Language Modeling) synthesis engine, and a TTS (Text-to-Speech) module. Through multi-agent system architecture and methodological design, this invention achieves modular processing, parallel retrieval tasks, and closed-loop security control. By enabling independent calls between input, output, agents, and inference stages via multi-layered security barriers, the system effectively mitigates risks such as prompt word injection, indirect injection attacks, harmful content generation, and information leakage. Sensitive information identification, access permission verification, and content compliance review are embedded in each stage of input, retrieval, information synthesis, and output to prevent sensitive data leakage and meet the application requirements of high-security business scenarios (such as finance, telecommunications, and government services).

The application discloses a wireless communication security transmission method, and belongs to the field of wireless communication security. The method comprises the following steps: an information sender encodes information to be sent to each legal receiver into a code word on a fine lattice by using a nested lattice code, wherein a secret message and an auxiliary message are generated for each information, the auxiliary message is a lattice point randomly selected from a coarse lattice, and the secret message is formed by mapping a mapping function to a coset of the coarse lattice; a precoding technology is used to isolate the information to be sent to each legal receiver, and a final sending signal is generated; and a legal receiver decodes the received signal to obtain the message to be sent by the information sender. The method uses a nested lattice code encoding scheme to minimize the information leakage rate of an eavesdropper, so that strong security of a communication system is achieved. Meanwhile, the secret message transmission between legal channels is realized by using a multi-user precoding technology, and the data security transmission between each point in a communication network is realized.

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.

This utility model relates to the field of document holder technology, specifically an information anti-theft document holder, comprising a leather document holder. One side of the leather document holder has a pre-drilled groove, inside which a leather core board is installed. A transparent document pocket is sewn onto one side of the leather core board. A leather bag is sewn onto one side of the leather document holder, and a transparent protective film is embedded on one side of the leather bag. A leather panel is sewn onto the other side of the leather document holder. A leather protective panel is sewn onto the top side of the leather panel, and a shielding layer is glued to the side of the protective panel close to the leather panel. Through the leather bag, transparent protective film, leather core board, and transparent document pocket, ordinary work permits and documents / work permits with important information can be stored separately, facilitating presentation while protecting privacy and preventing information leakage. The leather protective panel with a shielding layer covering the leather panel can prevent the information on bank cards and ID cards from being swiped.

The application discloses an identity card offline intelligent identification and correction system for public security actual combat, relates to the technical field of image processing and artificial intelligence, and comprises an image input module, an image correction module, an OCR identification engine module, an intelligent field extraction module, a backend reasoning core, a front-end interaction interface, a standardized output module and a local storage unit, and all calculations are completed on a local terminal and are independent of a network; the overall execution process is as follows: S1, image input; S2, certificate detection and correction; S3, text detection; S4, character recognition; S5, field extraction; and S6, result output. The identity card offline intelligent identification and correction system for public security actual combat adopts a full offline localization architecture, all image acquisition, model reasoning, data identification and result output are completed on a local terminal, are independent of a network and do not upload to a cloud, the risk of public security sensitive information leakage is avoided from the root, and the data security and confidentiality are significantly improved.

This disclosure relates to a risk determination method, apparatus, electronic device, and medium. The risk determination method includes: acquiring application information from an application; determining risk information of the electronic device based on the application information; and sending the risk information to the application. Since the application does not need to determine the risk information and there is no need to share information, more information from the electronic device can be combined when determining the risk information, thereby improving the accuracy of the risk information. Simultaneously, since only the risk information needs to be sent to the application, and there is no need to send information from the electronic device to the application to avoid privacy information leakage, the security of risk determination is improved.

The application discloses a kind of dike damage animal information acquisition method, system, equipment and storage medium.It includes: obtaining the authorized account information input by patrol officer, the authorized account information is checked, when checking, access permission is determined based on authorized account information;Obtain the project list corresponding to access permission, and determine target project from project list;Based on target project, obtain patrol information;The patrol information is checked, and after checking, it is stored in census database as patrol record.Through checking authorized account information to determine access permission, data access range can be accurately controlled, information leakage and disorderly operation are avoided, and system use safety is guaranteed.Through obtaining patrol information based on target project, data and project accurate binding are realized.Through checking information and storing in census database, data format is guaranteed to be standard, complete and effective, structured storage is realized, and reliable data support is provided for subsequent management analysis.

The present application relates to a compact Merkle tree zero-knowledge circuit judicial authentication method, comprising the following specific steps: registering identity attributes and constructing CPMT, authenticating anonymity / multi-factor and loading CPMT witness, generating CPMT-ZK proof and verifying on the block chain, cross-domain authorized access and reading end-cloud chain collaborative data, evidence solidification and generating a judicial verifiable chain link, the present application realizes the minimum disclosure of attribute and path information through zero-knowledge proof, avoids sensitive information leakage, reduces the risk of information abuse, reduces the proof generation and verification overhead through the optimized CPMT-ZK circuit and batch proof mechanism, meets the high-concurrency authentication and mobile terminal deployment requirements, through the quantifiable control of false positive rate, version management and digital evidence chain certificate support full-link traceability, recheckable, meet the requirements of judicial scene on compliance and accountability.

The application discloses an API automatic encapsulation method of MCP protocol adaptation, and belongs to the technical field of computers. The method realizes the cooperative execution and adaptive adjustment of format, security and semantic verification by dynamically evaluating the sensitivity of API response data and dynamically determining the multi-dimensional coupling verification strategy based on the evaluation result. Therefore, in the process of encapsulating the API into a standard MCP protocol tool, the problem of rigid verification strategy and lack of cooperation in each dimension in the traditional method can be avoided. The method ensures the data quality and call reliability of the encapsulated MCP protocol tool, reduces the risk of data format error, semantic deviation and sensitive information leakage, and improves the security and stability of the interaction between the artificial intelligence agent and the external system.

This invention relates to the intersection of cloud computing security, trusted computing, and hardware acceleration technologies, and discloses a virtual machine trusted state verification method and system based on TIPU. The method includes: configuring a measurement task on the host side of the TIPU, the measurement task containing the memory address information of the target virtual machine and its corresponding expected hash value; the TIPU directly reading the memory data of the target virtual machine via DMA based on the memory address information to generate an actual hash value; the TIPU comparing the actual hash value with the expected hash value to determine whether the target virtual machine is in a trusted state; when the virtual machine is determined to be in an untrusted state, the TIPU calls a built-in root of trust to sign the verification result and generate a remote proof report. This invention obtains the mapping table from the client's physical address to the host's physical address through the virtualization platform interface via a host agent and pre-configures it to the TIPU. The TIPU only accesses the target virtual machine's memory, achieving virtual machine context awareness and effectively avoiding cross-virtual machine information leakage.

A secure communication method and apparatus includes: a session management function network element receives first security capability indication information from a terminal device, where the first security capability indication information indicates that the terminal device supports establishment of a secure connection between the terminal device and a server. The session management function network element determines, based on the first security capability indication information, a first server that supports establishment of the secure connection. The session management function network element sends information about the first server to the terminal device to establish the secure connection. According to the method, a server that matches a security capability of the terminal device can be selected, to ensure security protection for communication between the terminal device and the server, avoid information leakage or tampering, and help improve information exchange transmission efficiency.

A semantically secure identification and communication method based on classical quantum channels comprises the following steps: constructing a classical quantum channel, selecting the input signal distribution and dividing the codeword, constructing an encoder, joint decoding, verification and identification, reliability analysis, and information leakage analysis. This invention divides the communication codeword into a main block and an auxiliary block. The main block uses an output statistical approximation of the transmission codebook, making it impossible for eavesdroppers to distinguish the communication signal from background noise. The auxiliary block uses a hash function for random mapping, preventing eavesdroppers from extracting valid information, thus achieving semantic security. Mapping the identification message to a combination of seed and hash value reduces the probability of confusion between different identification messages, improves identification accuracy, and provides a coding basis for analyzing false alarms, missed alarms, and information leakage. This invention has advantages such as strong confidentiality, strong concealment, high identification accuracy, and the ability to achieve identification communication while satisfying semantically secure requirements. It can be used for classical quantum secure communication.

The application discloses a called side video identity reverse authentication interaction method based on a video ringback tone, and the method is based on an existing video ringback tone service architecture, a call with an authentication request is initiated by a calling side, and a reverse authentication trigger instruction is carried in signaling by a ringback tone application server (AS). When a called terminal answers, a local live body detection and face recognition process is automatically triggered, and after feature extraction is completed at the terminal side, encrypted feature data is uploaded to a cloud end for verification. An authentication result generated by verification is real-timely returned through a signaling channel, and is dynamically displayed on a video ringback tone playing interface of the calling side. The application realizes real-time and high-trust biological feature verification on the identity of a called answering person in a native phone call, builds a two-way trust closed loop of the call, and effectively solves the problems of identity verification and information leakage protection.

The present application relates to the field of electromagnetic information leakage identification, and particularly relates to a kind of electromagnetic information leakage fast discrimination method and device based on time sequence information entropy waveform, greatly improve the efficiency and accuracy of electromagnetic information leakage discrimination.Solution includes: collecting electromagnetic leakage signal at different positions on equipment, establishing electromagnetic information leakage signal database;Based on information entropy, the degree of disorder of the time domain signal of the electromagnetic leakage signal is judged, and the time sequence information entropy value of the time domain signal at different positions on the equipment is obtained;The time sequence information entropy values of the time domain signals at different positions on the equipment are sequentially connected to obtain the time sequence information entropy curve of the overall structure of the equipment;The time sequence information entropy curve is analyzed, and if the time sequence information entropy curve is greater than the threshold curve, the electromagnetic information leakage of the equipment is judged by determining whether there is red signal component in the collected electromagnetic leakage signal.The present application is suitable for the rapid identification of electromagnetic information leakage.

The present application provides a kind of face video identification method and system, method includes: obtaining the video frame image sequence corresponding to face video, video frame image sequence is by multiple video frame images, and video frame image is obtained by frame by frame processing to face video;According to video frame image sequence, obtain the human heart rate feature and texture feature in face video;According to human heart rate feature and texture feature, determine the authenticity of face video.The system executes the method.The present application can significantly reduce the probability of identifying fake face video as real face video, can effectively prevent face spoofing attack and fake face video attack, reduce the risk of secret information leakage.

The application discloses a kind of digital identity and its account authentication method, device and storage medium, the method includes: generating authentication credential for the application of application authentication and return, to make the application authentication credential and business data acquisition request are sent to another application;Check authentication credential;After check pass, it is confirmed whether the application level digital identity account of the application authentication credential and the application level digital identity account of sending authentication credential correspond to the same person by trusted digital identity root, if yes, then authenticate application level identity information and generate authentication result;If not, then find the application level identity information corresponding to the same person again authentication and generate authentication result.The application binds the network certificate identification corresponding to network certificate platform by trusted digital identity root and network certificate, and uses trusted digital identity root to replace the role of plaintext identity information in the prior art, to realize the identity authentication between digital identity account of the same user in different applications, thereby reduce the risk of plaintext identity information leakage in the process of identity authentication.

This application discloses a new energy industrial control system platform with real-time early warning function applied in the sampling field. This system platform, through the setting of a zero-trust security model, is significantly different from traditional protection in that all entities in the network, regardless of whether they are on the external or internal network, are considered untrusted by default and require authentication and authorization. This allows for trust assessment and dynamic access control of all access from both inside and outside the enterprise, thereby achieving finer-grained access control, significantly reducing the network attack surface, and achieving the goal of protecting enterprise data resources. Furthermore, in conjunction with the setting of a network disconnection alarm strip, when access is made internally or externally or when a network attack occurs, the central controller controls the network disconnection alarm to inflate, disconnecting the network cable on the target access terminal, thus effectively preventing information leakage and improving confidentiality. Simultaneously, the audible and visual alarm is activated, providing real-time early warning of potential information leakage risks.

Embodiments check that a debugging mode of a code enables a data protection compilation; load a debugging information entry with a new attribute having a true value in response to the debugging mode of the code enabling the data protection compilation; activate a debugging session of the code; parse the debugging information entry with the new attribute; determine that the new attribute has the true value in response to parsing the debugging information entry with the new attribute; generate an enhanced debugging reply packet with a protect flag having the true value in response to determining that the new attribute has the true value; and prevent access of a variable of the code in response to determining that the new attribute has the true value.

This invention presents a threshold-free, privacy-preserving federated learning poisoning attack defense method, addressing the technical problems of intermediate information leakage, difficulty in distinguishing between benign and malicious updates, and difficulty in adapting to high-attack-ratio scenarios. The implementation includes: initialization; training and uploading parameters; secure K-means clustering on the server and threshold-free filtering based on benchmark gradients; server aggregation and dynamic benchmark updates; and updating the number of clusters. This invention uses a multi-party secure computation extension protocol to protect client gradient privacy in cluster-based federated learning poisoning attack defense. It designs a robust defense strategy of multi-cluster partitioning and combination filtering, performs secure K-means clustering, and securely compares different cluster combinations with server benchmark gradients. It does not require a preset malicious user ratio threshold and adaptively filters out benign update sets, achieving a balance between security, robustness, and scalability. It is applicable to federated learning systems involving a large number of heterogeneous entities, such as smart cities and connected vehicles.

This invention relates to the field of Internet of Things (IoT) technology, specifically to a data encryption method based on WiFi Mesh. The WiFi Mesh-based data encryption method includes the following steps: S1, a key exchange phase, where an unconnected node sends a network access request to a connected node, and the connected node generates a public key A and a private key a using an asymmetric encryption algorithm; S2, the connected node sends public key A to the unconnected node, which generates a random key B using a random number, and encrypts the random key B using public key A to obtain ciphertext b; the broadcast key E is initially generated by the WiFi root node using a random number, and all WiFi Mesh network endpoints use the same broadcast key E; the unicast key F is randomly generated by the connected node. Compared with existing technologies, this invention has the following advantages: it solves the problem of sensitive information leakage during the initial key exchange in data transmission using an asymmetric encryption algorithm; it improves the starting point of the entire cycle, ensuring the security of subsequent data communication.

This invention discloses a data security access control method based on symmetric encryption, comprising the following steps: collecting access requests to generate access event sequences; constructing an access behavior graph, binding symmetric key increments, and generating access behavior graph data; calculating multi-scale topological feature encodings into an access behavior fingerprint set, and generating the region to which the access behavior fingerprint belongs; generating an attacker's cognitive state vector; calculating the session information leakage amount and generating an information leakage budget state; selecting a symmetric key subspace and generating a path working key; dividing encrypted data into a semantic field set and generating a candidate access view set; and executing data security access control: when authorized, selecting the authorized view to decrypt and generate the target data access view; when unauthorized, selecting the decoy view to generate the decoy data access view. This invention utilizes access behavior fingerprints and dynamic key control to achieve adaptive secure access control of encrypted data, possessing advantages such as strong anti-inference capabilities, high misleading potential, and refined authorization.

The application discloses a cooperative remote printing method and system based on a P2P network, relates to the technical field of printing methods, and can be widely applied in the manufacturing of computer peripheral devices such as man-machine interactive devices and graphic image output devices, and the manufacturing of electronic devices such as cloud platforms, Internet of Things, mobile intelligent terminals and intelligent medical systems. According to the method, nodes with matched business attributes are screened out according to a business execution strategy to form a compliance node set, and the mechanism ensures that a printing task is executed only on a printer that meets business rules such as a geographical position, organizational affiliation and security level, thereby solving the problems of information leakage or management confusion in the prior art. On the basis, further optimization selection is carried out in the compliance set according to real-time state information, and a target node with the optimal comprehensive performance is selected, so that the printing task meets the organizational management specification and the optimal execution performance is obtained.

The application relates to the technical field of intelligent household appliances, and discloses a remote control method and device for a television and the television. The television is provided with a WiFi sensing module. The remote control method comprises the following steps: in the case that it is determined that a user exists in a set area in front of the television, starting the WiFi sensing module to collect wireless signal change data caused by a user gesture action, and determining a multi-source data frame; based on a preset feature extraction algorithm, extracting individual biological features and gesture action features from the multi-source data frame; determining whether the user in the set area is an authorized user according to the individual biological features; in the case that the user in the set area is an authorized user, generating and controlling the television to execute a remote control instruction according to the individual biological features and the gesture action features. The application can reduce the risk of user privacy information leakage on the basis of realizing accurate remote interaction control of the television.

This invention discloses an artificial intelligence-based smart wearable security alert method and system, relating to the field of smart wearable security technology. The invention includes: risk perception, collaborative verification and evaluation, and tiered alerts and protection. Risk perception constructs a dynamic personal digital behavior profile by collecting multi-dimensional data from textile-generated smart wearable devices. Based on the identified abnormal activity types and combined with fingerprint authentication, it accurately identifies information leakage threat events, transforms these events into collaborative analysis requests, and assesses confidence levels through collaborative evaluation of similar devices. It then reversely determines the type of information leakage threat event and triggers tiered alerts based on the type and confidence level of the event. This supports proactive protection, countermeasures, and sharing of information leakage threat event type characteristics, solving the problems of traditional passive protection, limitations of single-device perception, and high false alarm rates, thereby improving the accuracy and proactivity of security protection for textile-generated smart wearable devices.

The application belongs to the field of bioinformatics and relates to a cell communication prediction method based on heterogeneous graph integration and dynamic fusion. First, ligand receptor features and labels are obtained and a heterogeneous graph is constructed, outer layer stratified cross-validation and training fold stratified validation are adopted, and only training feature standardization is based; second, a deep neural network branch outputting a prediction logarithm value is trained, and a first prediction probability is obtained through Sigmoid; third, a multi-random seed heterogeneous graph auto-encoding sub-model is trained, an AUC based on a current outer layer reserved evaluation set is monitored, and the optimal parameters are rolled back, the sub-model edge prediction probability is averaged to obtain a second prediction probability; then, the two branch results are ranked and normalized, and dynamic gating or weight search fusion is performed based on the AUC of the current evaluation set; finally, the final interaction prediction score or ranking result is output. The application can reduce the risk of information leakage, alleviate the output scale difference and weak branch interference, and significantly improve the model stability and generalization ability.

This invention discloses a browser-based automatic website login method, device, and electronic device. When the browser displays the login interface of any website, the target login credentials for the website are obtained. Based on the website's filling rules, the corresponding interactive simulation operation is determined. By executing the interactive simulation operation, the target login credentials are filled into the login interface to automatically log in to the website. This reduces the possibility of information leakage caused by saving login credentials locally in the browser and reduces information security risks.