88 results about "Information privacy" patented technology

A distributionally robust optimization method and apparatus for an electric-hydrogen-thermal integrated energy system, relating to the field of power system optimization operation. The method comprises: establishing a multi-agent optimization scheduling model of an electric-hydrogen-thermal integrated energy system; using a data driving-based distributionally robust optimization model to describe the source-load bilateral uncertainty of a power grid system agent optimization scheduling model, establishing a three-layer two-stage power balance model of a power grid system, and using a column and constraint generation algorithm for solving; and using an alternating direction method of multipliers to alternately iterate the three-layer two-stage power balance model of the power grid system, a hydrogen network system agent optimization scheduling model, and a heat network system agent optimization scheduling model, to realize distributed parallel solving of the multi-agent optimization scheduling model of the electric-hydrogen-thermal integrated energy system. Compared with the prior art, each agent scheduling scheme is solved by means of interactive iteration in the present method, thereby protecting the information privacy of each agent while improving the operation economy and reliability of an interconnected power grid.

The present disclosure relates to a system to proactively detect in real time one or more threats in crowded areas. The present disclosure presents a proactive system for real-time threat detection in crowded areas. Utilizing a network of imaging sensors and advanced machine learning algorithms, the system identifies suspicious individuals, objects, and behavioral patterns within a predefined area. The system detects potential threats such as individuals on watch lists, suspicious objects like unattended bags, and abnormal behaviors indicative of security risks, by continuously monitoring and analyzing images and video feeds. Upon detection, the system promptly notifies authorities, providing detailed information on threat location, suspected individuals, and behavioral analysis. Privacy-preserving measures, including encryption of facial recognition data, ensure compliance with privacy regulations. The present disclosure offers a scalable, efficient, and automated solution to enhance security measures, reduce response times, and safeguard public safety in dynamic urban environments.

A user behavior analysis system based on cloud side-end cooperation of a large language model is used for carrying out information collection, cloud side-end cooperation and user behavior analysis on mobile phones and computer equipment, and comprises an information collection module, a cloud side-end cooperation module and a user behavior analysis module. According to the invention, information acquisition is carried out on electronic data of mobile phone equipment, information privacy collaboration is carried out through the cloud side end module, and then user behavior analysis is carried out based on a large model, so that the defects of low collaboration efficiency, high user behavior identification false alarm rate and the like of an existing user behavior analysis system are overcome; the evidence obtaining efficiency and the user behavior analysis effect are effectively improved by introducing a cloud side-end cooperation and large language model, and the cloud side-end cooperation behavior analysis system which is high in efficiency, high in precision and light in weight is achieved.

The invention relates to the technical field of information security, in particular to a sensitive information privacy calculation multi-dimensional security risk evaluation method, which comprises the following steps of: cooperatively collecting sensitive data information by setting a plurality of distributed nodes, and constructing the collected sensitive data information into corresponding feature vectors; performing privacy calculation based on the constructed feature vector; performing multi-dimensional assessment of the security risk based on a recovery result of the feature vector; according to the method, the feature vectors are encrypted layer by layer by using a multi-stage differential privacy mechanism, original data exposure is avoided, the risk of privacy disclosure is reduced, and personalized encryption is realized by dynamically adjusting the noise variance, and privacy protection and data validity are both considered; meanwhile, a distributed dynamic key management and decryption mechanism is introduced, and the key is prevented from being maliciously inferred through multi-round decryption calculation; and dynamically dividing risk level intervals, automatically matching feature evaluation results, and quickly identifying risk levels.

The invention provides a privacy protection multi-task allocation method for an unmanned aerial vehicle crowdsourcing perception system, which combines addition secret sharing and homomorphic encryption to realize bilateral privacy protection of a task side and an unmanned aerial vehicle position. The task requester and the working party split a task position and a UAV departure position into two secret shares [.] 1 and [.] 2 by adopting an additive secret sharing mechanism respectively, and send the two secret shares [.] 1 and [.] 2 to the two independent service parties S1 and S2 respectively; the service party calculates an encrypted square Euclidean distance between the UAV and the task based on the shared share, and generates two distance matrix shares D1 and D2. On the basis, the two service parties cooperatively execute privacy comparison and a minimum index protocol under the optimized Paillier, and multi-task encryption shortest path distribution is realized in combination with a Hungary algorithm. According to the method, addition secret sharing is fused, Paillier encryption and task matching optimization are optimized, the total flight path of the UAV is remarkably reduced while position information privacy of the whole task allocation process is guaranteed, and good safety and deployability are achieved.

The invention provides an active power distribution network reactive voltage optimization method and related equipment. The method comprises the following steps: constructing a centralized optimization model; decomposing the boundary constraint conditions according to sub-partitions, and determining a sub-partition optimization problem; solving each sub-partition optimization model based on the sub-partition optimization problem, converting the sub-partition optimization model into a sequential quadratic programming sub-partition optimization model based on the solved first power flow solution, and determining each sub-partition matrix; extracting coupling information in adjacent sub-partition matrixes to obtain an optimization sub-problem about a Lagrange multiplier coefficient; determining the optimal search direction of each sub-partition; and correcting the first search direction by utilizing the optimal search direction, carrying out iterative updating until a preset condition is met, and ending optimization processing on the reactive voltage of the active power distribution network. According to the embodiment of the invention, in the calculation process, the partitions are mutually independent, only the coupling information of the adjacent nodes of each partition is exchanged, and the information privacy among the sub-partitions is protected.

An illustrative data storage management system uses a control layer that controls information content presented to users and ensures information privacy between diverse tenants and / or resellers who share the system. The system populates a relationship database as transactions roll in (intake processing), and uses information in the relationship database later when processing responses (output processing). The relationship database comprises associations between e.g., a company ID and any number of entities that were created by or on behalf of the company or that are related to the company's service in the system. The control layer parses raw results that are responsive to requests for information and prevents others' information from being included in the responsive message(s). The techniques disclosed herein are not limited to shared systems managed by service providers, and may be implemented in fully owned and operated systems to add security and privacy among diverse users and / or departments.

The invention discloses a watermark dynamic rendering method, a storage medium and computer equipment. The watermark dynamic rendering method comprises the following steps: generating a plurality of watermarks in a webpage; a mouse covering event responding to the watermark is triggered, and the watermark is hidden; the mouse removal event responding to the watermark is triggered, and the watermark is displayed again. Through the method, the webpage browsing experience of the user can be improved while the privacy of the webpage information is protected.

The invention discloses a mobile phone information privacy protection method and system based on big data analysis, and relates to the technical field of information security, and the method comprises the steps: collecting latest privacy protection requirements from an application market and / or a supervision department, extracting privacy protection terms, and generating a standardized privacy protection rule data set; after an encryption analysis result is obtained, a dynamic privacy protection rule file is generated in combination with big data analysis; for the dynamic privacy protection rule file, analyzing byte codes of a mobile phone application through an ASM framework, automatically modifying a sensitive API calling point, and inserting privacy monitoring logic; repackaging the modified sensitive API calling point into an APK file, and carrying out privacy monitoring verification on the application program; according to the method, encryption analysis and distributed training are adopted, safe sharing and processing of privacy data under participation of multiple parties are ensured, the protection strength of mobile phone information privacy is effectively enhanced, and the method is suitable for complex and changeable application scenes.

The invention relates to a supply chain management method, in particular to a circulation box full life cycle management method and system based on a block chain and a program product. According to the method, logistics event information is collected and layered splitting is carried out, three parallel block chains including a logistics main chain, a carbon evaluation side chain and a prediction side chain are constructed, cross-chain atomic writing is realized in combination with two-stage submission and BLS aggregation signature, the residual life and path of a circulation box are predicted by using a digital twin model, and a carbon quota is dynamically allocated through deep reinforcement learning, so that the residual life and path of the circulation box are predicted. And finally, the position information privacy is protected by means of zero-knowledge proof. The circulation efficiency of the circulation box, the carbon emission reduction transparency and the system safety are remarkably improved.

The invention discloses a power distribution network and micro-grid distributed collaborative planning method and system based on an improved target cascade analysis method. Comprising the following steps: considering power distribution network topology and security constraints, and establishing an upper-layer power distribution network planning model by taking the minimum total cost of power distribution network planning as a target; establishing a lower-layer multi-microgrid planning model by taking the minimum total planning cost of the microgrid as a target in consideration of the aggregation capability of the microgrid to various internal resources; and solving the power distribution and micro-grid collaborative planning model by adopting an improved target cascade analysis method. Aiming at the power grid planning problem under the background of multiple planning subjects in the future, the effect of integrating various distributed energy sources by the micro-grid is exerted, the planning resources of the micro-grid and the power distribution network are coordinated, and the planning cost of each planning subject is reduced. According to the method, internal power generation resources of the power distribution network and the micro-grid can be reasonably planned, collaborative planning is realized only by means of a small amount of information on the premise that global equipment information is not needed, information privacy of each planning main body is protected, and economical efficiency of each planning main body scheme is improved.

The invention belongs to the technical field of block chain ERP (Enterprise Resource Planning), and discloses an enterprise ERP management system based on a block chain, which realizes credible sharing through an alliance chain architecture of a block chain base layer, ensures sensitive information privacy through a zero-knowledge proof technology, and can establish cooperative trust without endorsement of a third-party mechanism; the intelligent contract of the supply chain cooperation unit automatically executes cooperation rules such as purchase and acceptance, and trust disputes caused by manual intervention are avoided; the intelligent contract engine drives the unit processes of supply chain, production, finance and the like to be automated, so that end-to-end linkage of purchase-production-finance is realized, and manual operation links are reduced; the dynamic contract updating function enables the enterprise to quickly adapt to the business rule change, and the online period of a new business scene is shortened; the digital twinborn technology of the production management unit is fused with the AI model of the data analysis center, so that the decision accuracy of production scheduling and inventory management is improved, the resource configuration is optimized, and the problems of solidified process and slow response of the traditional ERP (Enterprise Resource Planning) are solved.

The invention discloses a federated learning privacy protection and attack defense method, which relates to the technical field of artificial intelligence and information privacy security crossing, and comprises the following steps: a client performs training based on local data and generates update, dynamically allocates privacy budget by evaluating the contribution degree of each network layer to model performance, and finally performs privacy protection and attack defense. The method comprises the following steps: reducing noise at a key layer to retain the utility of a model, enhancing disturbance at a non-key layer to improve privacy protection, uploading an update after noise addition to a server, predicting an update to be submitted by a client based on a historical training process by the server, calculating a deviation value between an actual update and a predicted update, and constructing a behavior evaluation value by combining multiple rounds of deviations. The method comprises the following steps: identifying and isolating abnormal clients by utilizing clustering analysis, dividing normal clients into fixed groups for intra-group aggregation, periodically executing global aggregation to update a model, starting an intra-group recovery mechanism when abnormality is detected, and performing local retraining and reconstruction aggregation output by the normal clients in the same group, thereby realizing safe and efficient federated learning.

The present application provides a vehicle-road cooperative voice interaction system, comprising: at least one set of first directional sound-transmitting and receiving devices arranged along the lanes for covering at least one lane, forming directional sound coverage of a section of the lane as a coverage area; the vehicle is equipped with a second directional sound-transmitting and receiving device; wherein the first directional sound-transmitting and receiving device and the second directional sound-transmitting and receiving device are arranged opposite to each other; if it is detected that the vehicle is about to enter the coverage area, the first and second directional sound-transmitting and receiving devices are turned on in advance to form directional sound communication between the first directional sound-transmitting and receiving device and the second directional sound-transmitting and receiving device, thereby completing the directional transmission and reception of sound information of vehicle-road cooperation; the present application breaks through the limitation that there is no direct audio information communication between roads and vehicles, and the relevant management departments cannot obtain the information in the vehicle in the first time, and the vehicle cannot obtain the latest road information in the first time, thereby realizing vehicle-road cooperative communication to the greatest extent; the present application also breaks through the barrier of sound isolation caused by the good sealing of the vehicle to ensure information privacy.

The invention discloses an energy sharing mutual aid benefit balanced distribution mechanism among multiple micro-energy networks, which belongs to the field of multi-micro-energy network system operation scheduling, and comprises the following steps: S1, dividing micro-energy network groups and combined pairing according to a matching index of a comprehensive curve form and a distance of micro-energy network source and load data, and constructing a micro-energy network benefit objective function; s2, introducing contribution, cost and risk factors into a traditional Shapley value method model, and constructing an improved Shapley value method model; and S3, performing distributed optimization solution on the micro-energy network cooperation alliance based on an ADMM algorithm, and realizing benefit balanced distribution by adopting a cooperation game strategy of an improved Shapley value method model. According to the method, the interaction efficiency is improved by dividing the group through source load matching, the information privacy is protected by using the ADMM algorithm, fair distribution is realized by improving the Shapley value method model, and the method is suitable for collaborative optimization operation of a multi-micro energy network system.

An illustrative data storage management system uses a control layer that controls information content presented to users and ensures information privacy between diverse tenants and / or resellers who share the system. The system populates a relationship database as transactions roll in (intake processing), and uses information in the relationship database later when processing responses (output processing). The relationship database comprises associations between e.g., a company ID and any number of entities that were created by or on behalf of the company or that are related to the company's service in the system. The control layer parses raw results that are responsive to requests for information and prevents others' information from being included in the responsive message(s). The techniques disclosed herein are not limited to shared systems managed by service providers, and may be implemented in fully owned and operated systems to add security and privacy among diverse users and / or departments.

The invention belongs to the field of artificial intelligence security, and discloses a physical multi-scene figure information privacy protection method based on image disturbance shielding, which comprises a target figure image privacy protection module and a target figure anti-identification module. The target person image privacy protection module generates robust global disturbance according to a target person image release scene, and prevents an image from being identified by an artificial intelligence model after being maliciously acquired; and the target person anti-recognition module adds disturbance cheating to specific glasses selected by the target person, so that the target person cannot be correctly recognized by the artificial intelligence model. According to the method, efficient protection of the person information privacy is successfully realized, the method has relatively high attack resistance and practical application value, the technical level of personal privacy protection is remarkably improved, and an innovative solution and a practical direction are provided for the fields of information security and privacy protection.

The present invention proposes a mobile terminal system and method supporting decentralized AI. The system utilizes decentralized technology and blockchain networks to realize computing power and data sharing of mobile devices, while protecting user privacy and automatically motivating user contributions through smart contracts. The system mainly includes: a data processing unit that performs local AI model training; a decentralized network communication unit that supports the upload and download of data and model updates; a user interface unit that displays training progress and incentive information; a privacy protection unit that encrypts and desensitizes user data; and an incentive mechanism unit that automatically allocates incentives based on user contributions. By building a decentralized AI ecosystem, the present invention promotes the sharing of data and computing power resources and strengthens privacy protection.

The invention discloses an access control encryption and decryption method and system based on content detection, and belongs to the technical field of cryptography, and the method comprises the following steps: initializing a global parameter and a main private key by an access control strategy and a security parameter input by a central authority, and generating a trap door; and sending the main private key to a sender authority to generate an encryption key for the sender. And the sender encrypts the information by using the encryption key, and then sends a ciphertext to the purifier. And the purifier purifies the ciphertext, and broadcasts the purified ciphertext to all receivers. Except a sender and a receiver which conform to an access control strategy, corresponding information cannot be transmitted and received through the method. According to the scheme, through cooperation and cooperation of all participants, on the basis of ensuring sensitive information supervision efficiency, encrypted transmission and identity verification of user information are achieved, sensitive information and identity information privacy of users are fully protected, and therefore the technical problem that in the prior art, a stealing risk exists in sensitive information transmission and storage is solved.

The invention relates to the technical field of virtual power plants, in particular to a virtual power plant multi-class power resource collaborative clearing method considering uncertainty, and the method comprises the steps: constructing a hierarchical interaction architecture of a virtual power plant and a power grid for multi-class power resources provided by the virtual power plant for the operation of the power grid; constructing a virtual power plant operation model by taking an energy storage operation constraint, a micro gas turbine operation constraint, an electric energy transaction constraint, an electric power balance constraint and a multi-class electric power resource balance constraint as constraint conditions and taking minimization of the operation cost of the virtual power plant as a target; establishing a multi-virtual power plant multi-class power resource collaborative clearing optimization model; aiming at uncertainty of new energy output, introducing distribution robust opportunity constraints, and constructing a virtual power plant multi-class power resource distribution robust collaborative clearing optimization model; and considering information privacy of each main body and energy and information interaction among a plurality of virtual power plants, proposing a distributed solution algorithm fusing a bisection method and an alternating direction multiplier method, and solving the collaborative clearing optimization model.

The invention discloses a crowd sensing truth value discovery method based on privacy protection of a reputation value, and aims to improve the accuracy and robustness of a result by combining the reputation value in data aggregation calculation under the condition of protecting the identity information privacy of workers and the privacy of data contents. The system network is composed of a credible authentication center, a data requester, a service platform and a worker. A worker registers a pseudonym in a credible authentication center in advance and initializes a reputation value. And when participating in the task, the service platform inquires whether the reputation value of the worker meets the task requirement from the credible authentication center, and selects the worker to participate in the task when the reputation value meets the condition. After a worker submits collected data, on the basis of a disturbance factor and an Elgamal encryption algorithm, on the premise that data privacy of the worker is protected, a more accurate truth value is obtained in combination with a reputation value, and the reputation value of the worker is dynamically updated according to the quality condition of the submitted data, so that the worker is guided to select and calculate the truth value to improve the data quality.

The invention belongs to the technical field of coal mine safety authentication, and discloses a coal mine safety terminal mixed identification authentication system based on a private block chain, which uses the private block chain and a hierarchical consensus architecture, combines a PBFT and PoS mixed algorithm to distribute node differentiation weights, and gives a consensus verification negative right to a supervision node. The monitoring requirement is met while the decentralization characteristic is guaranteed, and dependence on a single central server is not needed any more; even if part of nodes break down or are attacked, the fog node self-organizing network can take over tasks quickly, authentication interruption of the whole system is avoided, and the high requirement for zero interruption of coal mine production is met. Meanwhile, a terminal full-life-cycle tracing chain is constructed by utilizing the characteristic that data on the chain cannot be tampered and a cross-chain hash synchronization technology, and a zero-knowledge proof and differential privacy algorithm is matched, so that authentication data is prevented from being tampered, sensitive information privacy can be protected, and responsibility tracing difficulty is reduced.

The present invention proposes a multi-modal distributed multi-objective hierarchical intelligent integrated energy system scheduling method, which combines a multi-layer distributed multi-objective consensus method and a multi-modal multi-objective intelligent method for the intelligent scheduling of the integrated energy system. First, the multi-layer distributed multi-objective consensus method in the proposed method is used to solve the problems of system calculation speed, robustness, and information privacy when the scale of the interconnected integrated energy system increases and the number of agents increases. Second, the multi-modal multi-objective intelligent method in the proposed method is used to solve the multi-modal characteristic problems in multi-modal multi-objective scheduling. The proposed method uses multi-region hierarchical parallel processing to improve the optimization speed of the integrated energy system, solves the problem that one Pareto front in the objective space corresponds to two or more optimal Pareto solution sets in the decision space in the multi-modal multi-objective scheduling problem, and provides diverse alternative solution sets.

The invention provides a patient information privacy protection method for a sharing system of a three-dimensional physical examination system, belongs to the technical field of data processing, and is used for effectively balancing the requirements of privacy protection and data sharing. The method comprises the steps that the electronic equipment obtains physical examination information of a patient, the physical examination information comprises a first type of target physical examination information, a second type of target physical examination information and a third type of target physical examination information, and the privacy protection priority of the first type of target physical examination information is higher than that of the second type of target physical examination information; the electronic equipment executes first security processing on the first type of target physical examination information to obtain first type of target hidden information, and the electronic equipment executes second security processing on the second type of target physical examination information to obtain second type of target hidden information; and the electronic equipment stores the first type of target hidden information, the second type of target hidden information and the third type of target physical examination information into a three-dimensional physical examination system sharing system.

The application discloses a face image privacy protection method based on attention and a generative adversarial network, comprising the following steps: step one, constructing a self-attention perception generative network; step two, constructing a spatial attention guide discriminant network; step three, determining an attention-generative adversarial network optimization objective function; and step four, training the attention-generative adversarial network and outputting a final result. The application can improve the utility of the de-identified face image by retaining more abundant details of the de-identified face image, generate a high-fidelity de-identified face image, and ensure that the privacy attribute cannot be detected and the user's personal information privacy cannot be leaked.

This application provides a method for protecting patient information privacy in a three-dimensional physical examination system sharing system, belonging to the field of data processing technology, to effectively balance the needs of privacy protection and data sharing. The method includes: an electronic device acquiring a patient's physical examination information, which includes first-type target physical examination information, second-type target physical examination information, and third-type target physical examination information, with the privacy protection priority of the first-type target physical examination information being higher than that of the second-type target physical examination information; the electronic device performing a first security processing on the first-type target physical examination information to obtain first-type hidden target information, and the electronic device performing a second security processing on the second-type target physical examination information to obtain second-type hidden target information; and the electronic device storing the first-type hidden target information, the second-type hidden target information, and the third-type target physical examination information in the three-dimensional physical examination system sharing system.

The present disclosure relates to a system to proactively detect in real time one or more threats in crowded areas. The present disclosure presents a proactive system for real-time threat detection in crowded areas. Utilizing a network of imaging sensors and advanced machine learning algorithms, the system identifies suspicious individuals, objects, and behavioral patterns within a predefined area. The system detects potential threats such as individuals on watch lists, suspicious objects like unattended bags, and abnormal behaviors indicative of security risks, by continuously monitoring and analyzing images and video feeds. Upon detection, the system promptly notifies authorities, providing detailed information on threat location, suspected individuals, and behavioral analysis. Privacy-preserving measures, including encryption of facial recognition data, ensure compliance with privacy regulations. The present disclosure offers a scalable, efficient, and automated solution to enhance security measures, reduce response times, and safeguard public safety in dynamic urban environments.

This invention discloses a personalized location trajectory privacy protection method based on mutual information, belonging to the field of crowdsourced sensing technology. It includes: Step 1: Data preprocessing; Step 2: After generating the Markov matrix in Step 1, the matrix is ​​normalized, and a location privacy protection mechanism is established by setting a distortion threshold and regularization parameters; Step 3: Measuring the effectiveness of location privacy protection. This method generates a Markov transition matrix by merging user location trajectory data, analyzes implicit privacy information and adds distortion perturbations, and uses mutual information to measure the degree of privacy leakage, achieving a trade-off between privacy and usability. It solves the problem that existing technologies cannot effectively overcome the risk of location information privacy leakage.

The present disclosure relates to a system to proactively detect in real time one or more threats in crowded areas. The present disclosure presents a proactive system for real-time threat detection in crowded areas. Utilizing a network of imaging sensors and advanced machine learning algorithms, the system identifies suspicious individuals, objects, and behavioral patterns within a predefined area. The system detects potential threats such as individuals on watch lists, suspicious objects like unattended bags, and abnormal behaviors indicative of security risks, by continuously monitoring and analyzing images and video feeds. Upon detection, the system promptly notifies authorities, providing detailed information on threat location, suspected individuals, and behavioral analysis. Privacy-preserving measures, including encryption of facial recognition data, ensure compliance with privacy regulations. The present disclosure offers a scalable, efficient, and automated solution to enhance security measures, reduce response times, and safeguard public safety in dynamic urban environments.

The invention provides a multi-time-sequence integrated energy system control optimization method considering autonomy and collaboration. According to the method, through collaborative optimization of an IMES system operator and autonomous optimization of each MES superior coordinator, economic mutual aid is realized on the premise of ensuring the operation right and information privacy of each MES, the collaborative planning problem among multiple energy systems is effectively solved, and the efficient scheduling and dynamic adaptive capacity of the systems is improved. The power consumption cost minimization under different time scales is used as a target function, the consideration of factors such as the uncertainty of energy supply and demand response is realized, the economy and reliability of the system are improved, the peak load demand and the overall energy consumption are effectively reduced by the system autonomous adjustment and collaborative optimization mechanism, and the energy-saving and consumption-reducing effects are remarkable.