139results about How to "Avoid data breaches" patented technology

The invention provides a private domain live broadcast data storage and visitor authentication method and system based on a block chain, and relates to the technical field of data storage and access control, and the method comprises the steps: collecting multi-mode biological characteristic data of a visitor, carrying out the feature extraction and fusion through a deep neural network of a space-time attention mechanism, and carrying out the authentication of the visitor; authenticity verification is carried out in combination with an adversarial generative network, a dynamic identity token is generated, and a hash value of the dynamic identity token is written into the block chain. The method comprises the following steps: performing semantic analysis on live broadcast data flow through a self-adaptive content perception model, constructing a double-layer access control matrix according to a data sensitivity level and a credibility score, performing self-adaptive fragmentation and hierarchical encryption based on federated learning, and then storing. After an access request is subjected to identity verification, an optimal edge node is selected according to access authority and network performance parameters to construct multi-path transmission, and a transmission strategy is generated based on a service quality score and a data sensitivity level. And when the service quality is lower than a threshold value, triggering the smart contract to perform fault migration.

The invention discloses a customer information management system based on enterprise information security monitoring, which relates to the technical field of information security management and comprises an information management center. The information management center is in communication connection with an information collection and storage module, an information synchronization and sharing module, a safety evaluation module, a data access monitoring module, an abnormal behavior analysis module and a risk management module, and all the modules are in electric signal connection; the information collection and storage module is used for receiving client information input by a client through a client terminal. According to the method, comprehensive risk assessment and early warning are provided by analyzing a comprehensive result of security assessment, data use monitoring and abnormal behavior analysis, so that an enterprise can identify and assess potential security risks in time and formulate corresponding risk management strategies, and the risk management efficiency is improved. The division of risk early warning levels provides a quantitative risk view for enterprises to assist the enterprises in identifying and coping with potential security threats.

The invention relates to the technical field of system security, in particular to a computer storage file protection system which comprises a risk analysis module, a dynamic encryption module, an authentication management module and a behavior monitoring module. According to the method, the response speed and the personalized protection level of the file security are improved by automatically collecting location, time and user information parameters and executing context risk logic analysis, the system can provide customized protection schemes for different security requirements by dynamically adjusting an encryption mechanism and the key length, and the security of the file is improved. The system is allowed to strengthen protection measures under the high-risk condition, resource use is optimized under the low-risk condition, unnecessary performance burdens are avoided, through real-time monitoring and behavior analysis, the system can recognize and respond to abnormal behaviors in time, unauthorized access and data leakage are effectively prevented, potential threats to sensitive information are reduced, and the safety of the system is improved. The overall security management capability of the system is improved, and the continuity and effectiveness of data protection are ensured.

The invention discloses an automatic auditing and analyzing method for cultivated land soil data. The method comprises the following steps: S1, acquiring original soil data through multi-spectral imaging of an Internet of Things sensor and an unmanned aerial vehicle to form a data set; s2, using an extended Kalman filter to reduce noise and remove abnormal values, and using time sequence interpolation to complement missing data; s3, analyzing and auditing the preprocessed data based on the time sequence, and identifying an abnormal mode; s4, analyzing and fusing auditing data by using a causal reasoning graph neural network; s5, performing multi-dimensional analysis and prediction on the fused data by applying a big data analysis technology; s6, realizing real-time data visualization and interactive display through a visualization method driven by quantum computing; s7, using a natural language generation technology to generate a report for the soil data set and the analysis result; and S8, implementing encryption and access control in the data processing and transmission process. The invention provides a comprehensive soil data processing solution, and the data auditing efficiency, accuracy and safety are effectively improved.

The invention discloses a hardware cryptographic module based on a domestic commercial cryptographic algorithm and an implementation method of the hardware cryptographic module. The hardware cryptographic module comprises a security chip, a central control unit, a memory unit, a key management module, an encryption and decryption module, a multi-interface support unit, a bus interface unit and an indicator light module, the implementation method comprises the following steps: activating multi-layer encryption when a module is started, verifying the integrity of a master key through an SM3 algorithm, and ensuring the secure storage and management of the key; generating a session key by using an SM2 algorithm, and distributing the session key through a secure channel; performing multi-level encryption and decryption operation on the data, and introducing multiple authentication in key access; according to the invention, through multilayer encryption and multi-factor authentication, the security of key management is significantly enhanced, and through optimizing encryption and decryption processes and hardware configuration, the problem of performance bottleneck in a high-load environment is effectively solved, and efficient and safe operation of the system in a complex application scene is ensured.

The invention relates to the technical field of substation control, in particular to a substation control system based on cloud control and a local area network. Comprising a substation data acquisition module, a data analysis module, a cloud cooperative control module, an edge calculation response module and a safety guarantee module. The substation data acquisition module acquires multi-dimensional data through a local area network, and the data analysis module identifies abnormal and fault modes by adopting a dynamic multivariate autoregression tree algorithm. The cloud cooperative control module performs global load scheduling by using a sparse distributed optimization algorithm, and the edge calculation response module realizes rapid local response control based on a Markov random field model. And the safety guarantee module is combined with deep learning and a multi-factor identity authentication technology to ensure data transmission safety. According to the invention, the automatic control level and the overall operation efficiency of the transformer substation are improved, and efficient, stable and safe intelligent power management is realized.

The invention belongs to the technical field of distributed databases, and particularly relates to a decentralized copy control method of a distributed database, which comprises the following steps: step 1, copy management: determining the number and storage positions of copies according to data volume and system load requirements, and reasonably distributing data copies to different nodes; 2, replica consistency: selecting a consistency model to balance system performance and data consistency requirements; 3, synchronizing the copies: determining a data synchronization strategy between the copies, and adjusting according to the real-time requirement of the system; 4, conflict detection and resolution: detecting data conflict by using a timestamp, a version number or a logic clock mechanism, and designing a conflict resolution strategy; and 5, replica recovery: monitoring the state of each node, quickly detecting replica faults, and recovering data from other replicas. The stability, reliability and performance of the distributed database system can be effectively improved, and the distributed database system adapts to constantly changing service requirements.

The invention is applicable to the field of game security, and discloses an isolated storage and encryption method for game data, which comprises the following steps: classifying the game data according to the sensitive degree of the game data; encrypting the game data with high sensitivity, and selectively encrypting the remaining game data; storing the encrypted game data in a partitioned manner; controlling access to the encrypted game data through an authority management module; when a user accesses the encrypted game data, a corresponding decryption algorithm is used for decryption; wherein during encryption, the game data are encrypted according to the correlation between the game data. And the encryption key is generated by using the correlation between the data, so that the encryption process is more complex and is difficult to crack. An attacker not only needs to crack a single encryption key, but also needs to understand and simulate association logic between data, so that the attack difficulty and cost are greatly increased.

The invention discloses a wind power master control system based on a safe and credible software and hardware platform, which belongs to the technical field of wind power generation and comprises a data acquisition module, a data analysis module, a monitoring result judgment module, an abnormal unit optimization control module and a data backup module. According to the invention, the data acquisition module acquires the operation monitoring parameters of the wind turbine generator in real time, and the operation monitoring parameters are processed by the data analysis module to obtain the operation monitoring evaluation value, so that the operation state of the wind turbine generator is accurately judged, and accurate monitoring and timely early warning of the wind turbine generator are realized; the problem that in the prior art, a wind power master control system is insufficient in safety performance and reliability is effectively solved, and the safe operation level and the fault handling capacity of a wind power plant are improved.

The invention provides an RAG question setting and automatic question judging system based on a large model, and belongs to the technical field of intelligent education of natural language processing. The problems that in the prior art, efficiency is low, accuracy is insufficient, and safety and expansibility are limited are solved. An overall framework is established based on RAG, and a large model local deployment and fine adjustment module, a teaching resource vectorization storage module and a large model question setting and judging module are arranged under the overall framework; the large model local deployment and fine tuning module is used for realizing data collection and preprocessing, model selection and loading, task fine tuning, model training and verification and localized deployment and reasoning optimization; the teaching resource vectorization storage module is used for realizing data uploading and storage, data vectorization processing and data auditing and monitoring; the large model question setting and judging module is used for realizing question generation and automatic question judgment; the method is applied to wisdom education.

The invention belongs to the technical field of cloud storage, and particularly relates to an enterprise service management cloud storage system which comprises a system initialization module, a distributed data storage module, a data encryption module, an authority control module, a multi-level cache module, a data backup and recovery module, a log monitoring module and a task scheduling and dynamic extension module. The distributed data storage module is responsible for dividing data in enterprise service management into a plurality of data blocks; the data encryption module is used for encrypting the enterprise service data stored in the cloud; the authority control module is responsible for managing the access authority of the user to the data; the multi-level cache module accelerates data access by configuring a local cache and a global cache; the data backup and recovery module is responsible for backing up the stored data regularly; the log monitoring module records various operation logs of the system; and the task scheduling and dynamic extension module is used for dynamically distributing calculation and storage resources according to the priority of the task and the utilization rate of the system resources.

The invention relates to the technical field of block chains, in particular to a distributed Internet of Things management method and system based on edge cloud computing. The system comprises an intelligent data acquisition module, a self-adaptive data synchronization module, an access control module, a block chain optimization module and a security authentication module. The intelligent data acquisition module collects equipment data in real time, and the adaptive data synchronization module realizes cross-regional synchronization based on a HyperSync technology. The access control module intelligently distributes user and equipment requests by using a HyperAgent technology and transmits the user and equipment requests to the block chain optimization module, and the block chain optimization module optimizes the data processing performance of block chain nodes through a Hyper I O technology. And the security authentication module is combined with a dynamic key and a zero-trust authentication mechanism to realize multi-level application and equipment security authentication. According to the invention, the real-time performance of Internet of Things management, the stability of cross-regional synchronization, the intelligence of request processing, the efficiency of block chain operation and the overall security of the system are improved.

The invention relates to the technical field of information security, in particular to an information security cloud computing platform based on an intelligent computing center, which comprises a user identity and access control module, a self-adaptive threat detection module, a data protection and backup module, a virtualization and resource management module, an edge computing collaborative security module and a security event management module, the user identity and access control module performs identity verification and management; the self-adaptive threat detection module automatically analyzes and identifies novel security threats; the data protection and backup module encrypts the stored and transmitted data; the virtualization and resource management module manages and monitors the security state of the virtual machine; the edge computing collaborative security module deploys a security agent at an edge node; and the security event management module records security events of the platform. According to the method, the accuracy and real-time performance of threat detection and response are improved, and efficient and safe operation of the platform is ensured.

The invention provides an intelligent cold station control system based on machine learning, which relates to the technical field of energy and power engineering and is divided into an infrastructure part and an intelligent auxiliary part, the infrastructure part comprises a data acquisition subsystem, a data analysis and preprocessing subsystem, a machine learning model training subsystem, an intelligent control strategy generation subsystem, a real-time monitoring subsystem, a fault diagnosis and early warning subsystem, a man-machine interaction subsystem, an energy management subsystem and a communication subsystem. The intelligent auxiliary part comprises a self-adaptive optimization subsystem, a load prediction subsystem, an equipment health assessment subsystem, an intelligent cooperation subsystem, a virtual simulation subsystem, a green energy access subsystem and a safety protection subsystem, and the energy management subsystem generates output of the subsystems according to an intelligent control strategy and performs optimization management on energy consumption of the cold station. Through precise load prediction, intelligent control strategy generation and energy management optimization, the energy consumption of the cold station is reduced, and energy-saving operation is realized.

The invention relates to a smart power grid deep learning model copyright protection method, device and system based on a model confidence domain, a computer readable storage medium and a computer program product. The method comprises the steps of obtaining a smart grid depth model set; aiming at each model in the intelligent power grid depth model set, searching a characteristic data sample of which the model prediction value is close to the model discrimination boundary in the special data set to obtain a confidence domain characteristic point set; carrying out dimensionality reduction on a gradient vector of the confidence domain feature point set on a model discrimination boundary according to a linear discriminant analysis method to obtain a disturbance vector of the confidence domain feature point set; generating a model feature identification set corresponding to the intelligent power grid deep model set according to the prediction label change before and after the confidence domain feature point set and the disturbance vector are combined by each model; and training a to-be-trained copyright detection model according to the model feature identification set to obtain a pre-trained copyright detection model. By adopting the method, the detection accuracy of the model copyright infringement attack can be improved.

The invention discloses an interpretable medical big data dynamic security protection method. The method relates to the technical field of security technology digital processing, and comprises the following steps: collecting and processing infectious disease patient data; performing classification and encryption processing; monitoring the encrypted data in real time; obtaining an infectious disease patient identity information data encryption security assessment index, an infectious disease patient movement path key management security assessment index and an infectious disease patient electronic medical record data leakage risk assessment index; and comprehensively analyzing, evaluating and adjusting. According to the method, medical big data dynamic safety protection performance evaluation analysis is performed on the encrypted data of the infectious disease patient, and the medical big data dynamic safety is adjusted according to the comprehensive evaluation result, so that the interpretable medical big data dynamic safety protection dynamic capability is improved; the problem that in the prior art, the explainable medical big data dynamic security protection dynamic capability is insufficient is solved.

The invention discloses an encryption method for nondestructive testing of a DICOM (Digital Imaging and Communications in Medicine) image file, which comprises the following steps of: reading the DICOM file, acquiring image data information and other data element information and inputting; performing feature extraction on the input information to obtain a feature sequence; preprocessing the feature sequence into an initial value required by three-layer chaotic mapping; constructing a chaotic mapping function according to a three-layer mode; processing the initial value obtained by preprocessing to obtain encrypted image data; symmetric encryption is carried out on other data element information of the DICOM file to obtain a secret key; symmetrically encrypting all data element information except the image to obtain an encrypted data sequence; and recombining the encrypted image data and the encrypted data sequence to obtain a DICOM encrypted file. According to the method, a mode of combining multi-level chaotic mapping and symmetric encryption is adopted in the encryption process, and the effect of comprehensively protecting image information and other data element information in the DICOM file can be achieved.

The invention provides a cross-domain user login system, method and device based on a quantum key distribution network, and the system comprises an access routing service which is used for routing a user request to a corresponding service center; the plurality of service centers are used for receiving and processing user requests and sending key requests and identity authentication requests to the corresponding quantum cryptography service modules; the quantum cryptography service module is used for providing an encryption key for the key request and performing identity authentication for the identity authentication request; the quantum exchange cipher machine is used for receiving the quantum key sent by the quantum random number generator and providing a key service, the quantum key pre-generated by the quantum random number generator is stored in the quantum exchange cipher machine, and the quantum key and the quantum security key stored in the quantum security chip are symmetric keys; and the quantum key distribution module is used for enabling two communication parties to generate and share the same quantum key based on a quantum key distribution protocol, and encrypting and decrypting based on the quantum key. According to the invention, the multi-center scene communication security is improved.

The invention discloses a multi-level control method based on Internet information security, and the method comprises the steps: constructing a community smart screen playing mode judgment model, and determining the playing modes of a community smart screen in a use peak period and a non-use peak period; the network module is used for cutting off the connection between the community smart screen and an external network in a non-use peak period, and obtaining a latest playlist of the community smart screen in a random networking mode; using a community smart screen playing mode judgment model to determine a playing mode of the community smart screen during holidays and festivals; determining an optimal playing mode in the current scene by using a community smart screen playing mode judgment model; and identifying abnormal activity information according to the network flow data and the access log, disconnecting the network connection of the community smart screen, and entering a physical isolation state. Through the multi-level control method, accurate content playing, dynamic adjustment and efficient safety management of the community smart screen are achieved, and the network safety and operation stability of the community smart screen are effectively guaranteed.

The invention discloses a power grid marketing data penetration analysis and operation management method and system, and relates to the technical field of power system operation management, and the method comprises the steps: constructing a data label and index library, and carrying out the layered collection and unified arrangement of electricity charge data; developing a penetration analysis model, and realizing business whole-process visualization based on micro-service; a multi-service system is integrated, and a dynamic security policy is deployed to guarantee data and application operation. The method improves the accuracy and efficiency of data processing, enhances the transparency of a business process, optimizes the use of data storage and computing resources, improves the safety and stability of the system, achieves the efficient utilization of power grid marketing data and the optimization of operation management, improves the operation management level of a power enterprise, and also improves the safety of the power enterprise. And reliable data support is provided for enterprise decision making, so that sustainable development of enterprises and improvement of market competitiveness are promoted.

The invention discloses a rapid batch switching authentication method for predictability and aggregation promise proof, which realizes batch authentication of a plurality of user terminals by generating system parameters and secret keys through a trust mechanism and combining predictability promise and aggregation signature technologies. In the authentication process, the edge base station to be switched exchanges with the current communication edge base station through an encrypted message, verification information such as a pre-authentication certificate and a signature is generated through the user terminal, and identity authentication is completed step by step. The method comprises the following specific steps: a trust mechanism generates a private key, a public key, a pseudo identity and an expiration timestamp for each device; through multiple rounds of message exchange, the edge base station and the user terminal perform identity verification by using a shared key and a hash function; and finally carrying out efficient verification on a plurality of users through batch signature and aggregation commitment. According to the method, on the basis of ensuring the security, the speed of switching the authentication process is greatly improved, and the method is suitable for a large-scale network environment, especially in edge computing and mobile communication networks.

The invention provides a login method and system based on a 5G message voiceprint verification code, and the method comprises the steps: generating a 5G message, receiving a message receiving confirmation feedback of a user, obtaining a composite audio stream through combining with environment sound collected based on a local voiceprint collection device, carrying out the processing through a blind source separation algorithm, obtaining a preliminary composite voiceprint sample, and carrying out the verification of the voiceprint verification code. A target composite voiceprint sample is obtained after optimization; performing encryption processing based on a preset encryption protocol, obtaining a decrypted target composite voiceprint sample in combination with a quantum key distribution mechanism and a cloud authentication platform, and calculating a preliminarily adjusted comprehensive score by using a convolutional neural network, a recurrent neural network and a generative adversarial network combination model; performing processing by utilizing a behavior analysis algorithm to obtain a final adjusted comprehensive score, and performing access permission confirmation to obtain an access confirmation result; according to the invention, the security and accuracy of user identity verification are enhanced, efficient user experience is provided, and the security and reliability of the user login process are ensured.

The invention discloses an APP interface security verification method and system in an iOS mixed mode, and the method comprises the steps: enabling an APP to initiate a request to a server side, obtaining a current security verification code and validity period information, and storing the security verification code and the validity period information in a data storage region of the APP; intercepting a native network request and a WebView network request of the APP to obtain a first network request; obtaining a security check code in a data storage area of the APP, and checking the rule to generate a security check parameter; modifying an interface domain name in the first network request, and respectively adding the security verification parameter to the corresponding first network request to obtain a second network request containing an encryption parameter; performing security verification on the second network request at the server side according to the verification rule, and returning a verification result to the APP; and executing corresponding operation according to the verification result. The invention relates to the technical field of safety verification, and solves the problem of potential safety hazards of an interface under a mixed mode architecture.

The invention discloses a traditional Chinese medicine analysis and identification system, method, equipment and medium based on a large model, and the system comprises a data collection module which is used for collecting multi-dimensional data of traditional Chinese medicines, a data preprocessing module which is used for carrying out the cleaning, standardization processing and feature extraction of the collected data, and a data analysis module. The data processing module is used for analyzing and processing received data by utilizing a pre-trained deep large model, the result output module is used for outputting an analysis result to a user in a visual manner, and the analysis result output module comprises a visual chart, a detailed report form and an intelligent feedback module according to the feedback of the user on the analysis result and the actual application condition. Through multi-dimensional data acquisition, advanced preprocessing, deep large model analysis and the like, the practicability is improved by modules of accurate identification, intelligent feedback, collaborative analysis and the like of the traditional Chinese medicine, data updating and the like ensure that the system advances with the times, powerful technical support is provided for industrial development of the traditional Chinese medicine, and the quality and safety of the traditional Chinese medicine are guaranteed.

The invention relates to the technical field of data security protection, in particular to an encryption security protection system based on Internet data transmission. Comprising a data acquisition module, a server, a data encryption module, an identity verification module, a data verification module and a security protection module, by combining the authority level and the access frequency, the system can dynamically adjust the verification standard, so that the risk of the access request is more accurately judged, and the risk of unauthorized access is reduced; the method comprises the following steps: analyzing historical access behaviors of a visiting user, dynamically calculating a security value in combination with factors such as verification pass and failure times, access duration and risk access times so as to assess potential risks of user access, deciding whether to allow to continue to transmit data according to the security value, and sending out an early warning when the risk is relatively large; and the access is limited or an administrator is notified to carry out further processing, so that effective user behavior monitoring and risk management are realized, and the security of data transmission is improved.

The invention discloses a multi-modal file data co-processing management system, which relates to the technical field of file management and comprises a data input layer, a data storage layer, a data processing layer, a business logic layer, an application layer, an integration layer, a security monitoring layer and an infrastructure layer. The method not only supports management and processing of various data types, improves data inclusivity and processing capability, but also has real-time cooperation and version control functions, improves team cooperation efficiency, reduces data conflicts, ensures data integrity and consistency, simplifies data entry, classification, filing and retrieval processes through automatic tools and algorithms, and improves the efficiency of team cooperation. And meanwhile, an intelligent search function is provided, required data can be quickly positioned, a user can remotely access archive data from any place with network connection, the accessibility of the data is improved, the system also supports cross-department data sharing, and the circulation and collaboration of information are promoted.

The invention discloses a warehouse management method and system based on big data, and relates to the technical field of warehouse management, and the method comprises the following steps: 1, data collection and integration; 2, data storage and management; 3, data analysis and intelligent decision making; 4, real-time monitoring and process automation are carried out; and 5, performing performance evaluation and continuous improvement. According to the invention, intelligent decision making and efficiency improvement are realized, through real-time data analysis and prediction analysis, the system can provide real-time inventory state and future demand prediction, and an automatic process is realized, so that decision making quality and warehouse operation efficiency are improved, and human errors are reduced. The intelligent decision support system can provide scientific inventory management suggestions for managers according to historical data and market trends, ensure that the inventory level is matched with market demands, and avoid inventory overstock or shortage.

The invention provides a mobile intelligent cabinet based on multiple communication links, and the method comprises the steps: monitoring an environment parameter in the intelligent cabinet in real time, and transmitting a first early warning signal when the environment parameter does not accord with a preset environment parameter; and monitoring the material types in the intelligent cabinet and the stock quantity corresponding to each material type in real time, and sending a second early warning signal when the material types are less than a preset material type or the stock quantity corresponding to each type is less than a preset quantity; encrypting the first early warning signal and the second early warning signal to generate an encrypted signal; the receiving module is used for receiving and decrypting the encrypted signal, transmitting the encrypted signal, and receiving and decrypting the encrypted signal to obtain a decrypted signal; and generating a material supply route based on the decryption signal, and feeding back the material supply route to a predetermined target object. The material storage is monitored in real time, and the conditions of aging, corrosion and excessive purchasing of the materials are avoided.

The invention provides a multifunctional automatic embedded man-machine interaction system, which belongs to the technical field of man-machine interaction and comprises a core processor, a touch display screen, a sensor module, a communication module and a storage module, software covers a multi-mode interaction interface, an automatic task execution module, an intelligent learning and personalized recommendation module and a data security and privacy protection module, the touch display screen is a high-resolution multi-point touch screen, the sensor module comprises various sensors, the communication module has various connection modes, the multi-mode interaction interface supports various operation modes, and the multi-mode interaction interface supports various operation modes. The automatic task execution module can automatically execute tasks according to conditions, the intelligent learning and personalized recommendation module can provide personalized services, the data security and privacy protection module guarantees data security, the problems that an existing system is single in function and low in automation degree, and data security has hidden dangers are solved, and user experience and working efficiency are improved.

The invention relates to the technical field of digital information transmission, in particular to a network security protection encryption method and device, and the method comprises the steps: obtaining to-be-tested data and encryption algorithms, marking the to-be-tested data and encryption algorithms as target algorithms, collecting the test data of each target algorithm, and obtaining the performance evaluation index and security evaluation index of each target algorithm through processing; obtaining basic characteristic data of the to-be-encrypted data, and processing the basic characteristic data to obtain a data demand performance parameter and a data demand security parameter of the to-be-encrypted data; and performing comprehensive analysis to obtain a comprehensive energy efficiency evaluation index of each target algorithm, and performing encryption algorithm screening. According to the network security protection encryption method and device provided by the invention, the comprehensive energy efficiency evaluation index of each target algorithm is obtained through comprehensive analysis, and the algorithm which is more efficient in resource utilization can be selected, so that the waste of system resources is reduced, the overall efficiency and response speed are improved, and the user experience is improved. And the system fault risk caused by algorithm defects or insufficiency can be reduced.