11results about How to "Address privacy breaches" patented technology

The application provides a train operation and maintenance data privacy statistical method, system, medium, equipment and program product, relates to the train data processing field, and through first collecting operation and maintenance data and operation and maintenance data fragments of a train control center, taking the operation and maintenance data as original data into a database, and completing data confusion processing by relying on a data confusion protocol, then performing alignment processing on the confused data to obtain to-be-calculated data, so that a plurality of statistical calculation tasks such as data alignment, mean variance and Pearson correlation coefficient can be carried out. The application fills the blank of privacy calculation in the train data analysis field, realizes safe convergence and value mining of multi-source operation and maintenance data, and improves the train operation and maintenance data management capability.

This invention discloses a privacy-preserving method and apparatus for revenue sharing based on a Trusted Execution Environment (TEE), belonging to the field of privacy computing technology. The method includes: collecting traffic and revenue settlement data from multiple business systems, encrypting the data after standardized preprocessing, and transmitting it through a secure channel to a secure enclave within a Trusted Execution Environment (TEE); loading revenue sharing rules and generating a smart contract within the enclave, determining the accounting logic and constraints, performing isolated calculations on the encrypted data, obtaining the revenue sharing amount for each partner, and completing consistency verification; extracting key information to generate data fingerprints for on-chain storage, distributing the encrypted calculation results to authorized nodes, and completing closed-loop settlement. This invention utilizes a TEE to achieve encrypted closed-loop calculation, solving the privacy and trust issues in multi-party revenue accounting. Combining smart contracts and blockchain storage improves the efficiency, accuracy, and traceability of calculating billions of traffic data points.

The embodiment of the application discloses a kind of multi-party collaborative automatic driving traffic responsibility determination method and system, wherein the method comprises: real-time acquisition of the original data of each data source;Each original data is calculated by hash digest;After the accident, the relevant original data of the data source involved in the accident within the accident time period is obtained, the actual hash digest is calculated and compared with the hash digest for integrity check;Identity verification is carried out according to identity certificate;According to the ciphertext accident characteristics of the relevant original data, a space-time consistency graph is constructed, the deviation data of each data source and the abnormal data source mark are calculated;According to the equipment state data, the identity verification result, the integrity check result and the deviation data, the trusted weight of the corresponding data source is calculated;According to the ciphertext accident characteristics and the trusted weight, the responsibility proportion of each responsible party is obtained;According to the responsibility proportion, the trusted weight, the space-time consistency graph and the abnormal data source mark, a responsibility determination report is generated and is chained to store evidence. The responsibility determination efficiency and the reliability are improved.

The application discloses a data asset standardization packaging method and system and a storage medium, and belongs to the technical field of data processing. The method comprises the following steps: constructing a high-dimensional topological graph based on a business data domain, determining a core asset node set and an external associated node set in the high-dimensional topological graph; calculating the semantic gravity probability of each edge node in the core asset node set to each associated node in the external associated node set based on a semantic gravity field model, and marking the associated node with a semantic gravity probability higher than a preset threshold as a strong gravity boundary node; aggregating the weighted semantic features of all the strong gravity boundary nodes belonging to the same edge node to generate residual semantic metadata; and splicing and encrypting the residual semantic metadata and the naked data ontology of the core asset node set to generate a standard data asset package. The rationality of data asset packaging can be improved by the application.

The invention relates to a multi-mode classroom state evaluation method based on attitude motion gating. The method comprises the following steps: acquiring a high-definition video stream of a classroom scene; extracting a facial emotion feature vector and a human skeleton posture feature vector of the high-definition video stream, and destroying an original image frame of the high-definition video stream; encrypting and transmitting the facial emotion feature vector and the human skeleton posture feature vector to a cloud server; performing time sequence alignment on the facial emotion feature vector and the human skeleton posture feature vector, and generating a dynamic reliability gating factor based on the motion state of the human skeleton posture feature vector; utilizing a dynamic reliability gating factor and a multi-modal cross attention network, fusing the facial emotion feature vector and the human skeleton posture feature vector, and generating a space-time semantic feature; and determining a learning concentration level based on the spatio-temporal semantic features. According to the method, intelligent disambiguation of expression-posture conflict semantics in a complex classroom scene is realized by means of a dynamic reliability gating factor.

The invention relates to a display panel and a display device, and the display panel comprises a substrate which is at least arranged in a non-light-transmitting area; the light-emitting unit is arranged on one side of the substrate and located in the non-light-transmitting area. The at least one light blocking structure is arranged on the side, facing the light emitting unit, of the substrate, and the distance between the surface of the side, deviating from the substrate, of the light blocking structure and the substrate is larger than that between the surface of the side, deviating from the substrate, of the light emitting unit and the substrate; the orthographic projection of the light blocking structure on the substrate is at least partially located on the side, facing the light transmitting area, of the light emitting unit. At least part of the light blocking structure is arranged on the side, facing the light transmitting area, of the light emitting unit, and the height, in the direction away from the substrate, of the light blocking structure is designed to be larger than the height of the light emitting unit, so that the light blocking structure is located on a propagation path of large-viewing-angle light causing back light leakage as much as possible; therefore, most of the large-viewing-angle light rays are shielded, the light rays are prevented from entering the light-transmitting area, and the privacy leakage problem that information is visible from the back face is solved.

The utility model discloses a safe burglary -resisting door relates to the technical field of burglary -resisting door, the utility model discloses a burglary -resisting door body and the through groove : burglary -resisting door body is provided with the drawer groove corresponding with the through groove position, including: first slide rail, set up on the burglary -resisting door body, the number is two. The utility model discloses through the unique X type connecting mechanism and the coordination of many slide rail systems, forms stable load -bearing platform and line of sight shelter barrier when unfolding, effectively solved the privacy disclosure problem of traditional delivery mode, adopt the innovative embedded folding structure, through the accurate first slide rail, second slide rail and third slide rail system, make first board can be completely flush with burglary -resisting door body when closing, completely solved the problem of traditional external hanging type delivery device protruding door body, influence the beautiful problem, through the cooperation of T type guide slot and gyro wheel sliding block has guaranteed the smooth of sliding process, and the reinforcing rib and bearing design of X type connecting mechanism have effectively enhanced the structural strength.

The invention provides a mobile payment platform user privacy protection method and system, and relates to the technical field of mobile payment, and the method comprises the steps: triggering a data optimization process when the verification of a biological recognition system is successful but the matching score is low, carrying out the calculation in a random access memory of a device, and carrying out the high-intensity encryption of an increment parameter used for optimizing the biological recognition system, thereby achieving the user privacy protection. And the incremental parameters are not stored persistently. And then, instantaneously uploading the encrypted increment parameter to a server in a data stream form through a secure communication channel, and not writing the increment parameter into any local storage medium of the equipment in the whole process. And if the uploading fails, the encrypted increment parameter is destroyed from the random access memory immediately. According to the method, through full life cycle control from data generation, processing, transmission to destruction, non-persistent storage and instantaneous transmission of increment parameters are intensified in an emphasized manner, data are prevented from being traced in a local storage medium, the utilization risk of malicious programs is remarkably reduced, and the privacy security of mobile payment users is effectively guaranteed.

The application discloses a kind of high-efficiency casual neural network conversion methods, client and server side run preprocessing process in advance and obtain a set of matrix for encryption, client will generate matrix as key and use one-time encryption technology to encrypt original input data for prediction, send encrypted data to server side to calculate linear layer, server side will add Laplace noise to the result after linear layer calculation is completed and send back to client, then complete nonlinear function calculation in client, and the result is passed through noisy model Purifier, finally the result of noisy completion is returned to server side in plaintext form, server side gets plaintext and completes subsequent calculation of resnet101 network, finally completes prediction work.The method of the application can be applied to Resnet101 and other complex neural network models, and the privacy protection purpose is realized, which can greatly reduce the time required for prediction compared with the previous solution, and reduce the additional communication and additional calculation amount introduced by the encryption scheme.

The application discloses a longitudinal federated EBM commodity recommendation method with differential privacy protection, and comprises the following steps: 1, a master server uses a consumption feature data set to train an EBM recommendation model; 2, a slave server number is initialized; 3, the slave server uses the consumption feature data set to train the EBM recommendation model; and 4, whether the EBM recommendation model training is ended is determined according to the number of iterations. The application can effectively protect the user consumption feature information, thereby preventing the leakage of the user consumption feature information and providing effective commodity recommendation.

The invention provides an intelligent electric meter data security storage and tamper-proof block chain authentication method and system, and relates to the technical field of data security, and the method comprises the steps: receiving intelligent electric meter data, dividing a structured data object into a public fragment and a private fragment, executing zero-knowledge proof on the private fragment, and generating a mixed data carrier; establishing a cross-chain anchoring relationship, and synchronizing the Hash abstract of the mixed data carrier to a main chain and a side chain; triggering the smart contract to verify data validity; and verifying the data integrity through the global identifier when receiving the traceability request. According to the invention, secure storage and tamper-proof authentication of ammeter data are realized, sensitive data privacy is guaranteed, and data traceability and non-tampering are ensured.