197results about How to "Guaranteed credibility" patented technology

The invention provides a block chain data management method and system, and relates to the technical field of block chains, and the method comprises the steps: receiving and preprocessing an electronic file; encrypting the archive by using a public key and calculating a hash value; packaging the encrypted file and the hash value into a block chain transaction and broadcasting the block chain transaction; acquiring block information and safely storing the private key; verifying the integrity of the electronic file; recording a full life cycle operation log; the log is stored in an on-chain and off-chain combined mode; auditing the electronic file; and realizing access authority automatic management based on the intelligent contract. According to the method, the security, traceability and management efficiency of the electronic archives are improved.

The invention discloses a data security sharing method and system, and relates to the technical field of data security, and the method comprises the steps: receiving to-be-shared data uploaded by a data provider; fragmenting the data by adopting a biologically inspired adaptive fragmentation algorithm; generating a digital fingerprint for each fragment by using a multi-dimensional dynamic Hash algorithm; encrypting data fragments by adopting a post-quantum encryption algorithm and storing the data fragments in a decentralized network; recording the access authority, the digital fingerprint and the storage position information to a block chain security account book; when a data request is received, the access permission is verified; carrying out identity verification by adopting multi-mode biological feature recognition; after the verification is passed, obtaining a digital fingerprint and a storage position from the block chain; acquiring the encrypted fragments from the decentralized network and decrypting the encrypted fragments; verifying the integrity by using the digital fingerprint; and recombining the verified fragments to obtain complete data and returning the complete data to the requester. According to the method, efficient data sharing is realized while the data security is guaranteed, and the data value and privacy protection are effectively balanced.

The invention relates to the technical field of genomics, in particular to a gene detection data cleaning method and system based on artificial intelligence. The method comprises the following steps: acquiring gene detection data, and performing preliminary filtering on the gene detection data based on removal of low-quality reads to obtain preliminary filtering data; performing linker sequence identification and removal on the preliminarily filtered data, and performing sequencing error correction to generate gene sequence data; performing GC content analysis and repetitive sequence identification on the gene sequence data to obtain sequence feature data; performing dynamic quality threshold adjustment according to the sequence feature data, and performing secondary filtering on the gene sequence data to generate high-quality sequence data; and performing sequence pattern recognition on the high-quality sequence data to obtain sequence pattern feature data. According to the method, deep analysis is carried out by utilizing sequence characteristics such as GC content and nucleotide distribution, and the recognition capability on sequence complexity and variation modes is improved.

The invention relates to the technical field of dark green tea processing, in particular to a fermentation monitoring method in the dark green tea processing process. The method comprises the following steps: acquiring temperature sequences and oxygen contents of different monitoring positions of a fermentation box in a dark tea processing process; determining a corresponding fluctuation index according to the length corresponding to each sub-sequence section of each monitoring position and the fitting error of each data in the sub-sequence section; the temperature anomaly degree is obtained by combining the difference between the fluctuation indexes of the corresponding sub-sequence segments of each monitoring position and other monitoring positions and the temperature difference; integrating the temperature anomaly degree, the temperature change degree, the oxygen content change degree and the relative distance of the corresponding subsequence segments of each monitoring position and other monitoring positions to obtain contribution factors; and updating the temperature of the current moment based on the time interval between all the sub-sequence segments of all the monitoring positions and the current moment and the contribution factor. According to the invention, the accuracy and credibility of the temperature monitoring result in the dark tea processing process are improved.

The invention relates to the technical field of fault detection for a wireless communication network, and discloses a fault detection method for the wireless communication network. By collecting data of base station signal strength, network delay, data packet loss rate and user equipment signal quality, the problem of insufficient fault detection caused by a single index is solved. Through multi-dimensional data acquisition, the system can comprehensively evaluate network performance, the fault detection accuracy is improved, and different fault types can be effectively identified especially in a complex fault mode. By storing the data according to the time sequence, the problem of time sequence chaos is avoided, and accurate detection of time-varying faults is ensured. The comprehensive data vector generated by each time of sampling comprises a plurality of network performance indexes, so that the fault detection and positioning capability is improved. Abnormal values are eliminated through data preprocessing, the data quality is ensured, an accurate basis is provided for subsequent analysis, and the reliability of a detection result is ensured.

The invention discloses an SWMM simulation model approximation method based on sparse attention and physical embedding, belongs to the technical field of simulation modeling, and aims to effectively process high-dimensional time sequence input through a sparse attention mechanism and embed physical constraints to ensure physical consistency of model approximation and ensure that an output result conforms to the law of flow conservation and pollutant conservation. The SWMM behavior is accurately approached; according to the method, a complex simulation behavior of the SWMM is replaced by an efficient deep learning prediction model, the calculation efficiency is remarkably improved, the credibility of a prediction result is ensured, the method is suitable for a real-time simulation scene of regional drainage optimization, and real-time simulation support is provided for regional hydrological management.

The invention relates to the technical field of network security, in particular to a method and device for detecting illegal external connection of a terminal and a storage medium, and the method comprises the steps: obtaining all terminal equipment connected with a local area network, distinguishing authorized terminal equipment and unauthorized terminal equipment through authorization detection, and carrying out the risk grading of the authorized terminal equipment; the method comprises the following steps: generating an external connection behavior data set by combining client monitoring data, network layer monitoring data and intranet detection data, extracting key information such as an external connection target, access time, a protocol type and a port number, and dividing into pure intranet connection equipment, normal external connection equipment and unknown external connection equipment according to external connection permissions; inputting the log data of the unknown external connection equipment into the log anomaly detection model based on the Transform architecture, identifying an abnormal event, and calculating a log risk score; and if the log risk score exceeds a preset threshold, determining that the device is an illegal external connection device. According to the method, accurate detection of illegal external connection behaviors is realized, and the safety performance of a monitoring system is remarkably improved.

The invention relates to the technical field of safety monitoring of deep foundation pit construction adjacent to railways, and particularly discloses a safety monitoring device and method for deep foundation pit construction adjacent to railways. The system comprises a supporting structure safety analysis module, a settlement risk analysis module, a train passing construction safety evaluation module, a geological level risk evaluation module, a displacement level risk evaluation module, a database and a construction process construction safety evaluation module. Whether the construction of the deep foundation pit is safe or not is analyzed from the two levels of the safety change condition of the deep foundation pit when a train passes and the safety change condition of the deep foundation pit in the long-term construction process, that is, the deep foundation pit risk is automatically monitored from the four levels of the foundation pit supporting structure, the rail settlement risk, the foundation pit geology and the foundation pit displacement; the method avoids neglecting the instant safety risk, helps to evaluate the instant influence on railway facilities, and can grasp the overall safety trend, thereby helping to adjust the construction strategy and maintenance measures in time.

The invention discloses an urban street land fine division method and system based on deep learning, and belongs to the field of geographic information processing. The method comprises the following steps: firstly, collecting remote sensing image data, building space form data, business form POI data and urban land data of a case city district, extracting various kinds of information, converting the information into two-dimensional plane image format data, and carrying out rasterization and data enhancement processing; then training the land use division convolutional neural network deep learning model through a grid translation window method and a grid land use function judgment rule, performing rasterization function judgment on urban land use in a target area, dividing grid boundaries through a watershed method, and finally checking and correcting a result to obtain a target urban land use function judgment result. And obtaining a final result of land division of the target district. According to the method, the internal land of the urban land street can be finely divided, automatic division and function judgment of the urban land are realized, and digital and intelligent application conversion of urban planning work is promoted.

The invention discloses an intelligent logistics platform electronic signature automatic management method and system, and relates to the logistics management technology field, and a contract signing module of the system integrates a signature request unit, a first processing unit, a second processing unit, an electronic signature obtaining unit and a contract signing unit. Through the units, the effective verification of the user identity is realized, the dynamically encrypted and stored electronic signature is quickly obtained, and the security guarantee is provided for the contract signing process. In addition, the system also comprises a contract template management module, a signature management module, a contract generation module, a log and audit module, a user authority management module and the like, which jointly provide a comprehensive, efficient and safe intelligent logistics platform electronic signature automatic management scheme.

The invention discloses an asphalt viscosity testing device for road and bridge construction, and relates to the technical field of asphalt viscosity testing. Liquid asphalt reaching the detection temperature circularly flows between the heating mechanism and the viscosity testing mechanism, so that the asphalt can be continuously heated in the flowing process, the temperature of the asphalt is kept in a relatively stable state, and the inner walls of components such as a conveying pipe and a return pipe can be heated in the long-time flowing process of the asphalt, so that the viscosity of the asphalt is improved. Before the asphalt viscosity is detected, the temperature of the asphalt and the temperature of a component in contact with the asphalt can be kept consistent, so that the condition of heat loss before the asphalt is detected is avoided, and the accuracy of asphalt viscosity detection can be improved; the plurality of viscosity testing units are used for synchronously testing the viscosity of the asphalt at a plurality of positions at the same time, and the viscosity value of the asphalt at the testing temperature can be comprehensively evaluated, so that the condition that the testing data have relatively large deviation due to misoperation or equipment failure is avoided.

The invention provides a decentralized cross-chain user identity authentication method based on a password accumulator. The method comprises the steps that a representative node registers a cross-chain system identity for a user; the plurality of representative nodes jointly run a threshold signature protocol to generate an access voucher for the user; the relay chain verifies signature information and member certification information in the user cross-chain request based on the on-chain identity of the user and an accumulator, and if verification is passed, cross-chain transaction is allowed; and the representative node verifies the signature information and the member proof information in the user identity revocation request, if the verification is passed, the representative node and other representative nodes operate a threshold signature protocol together, and the proxy chain management node issues revocation elements and updates the accumulator. By utilizing the scheme of the invention, the user identity can be quickly verified in a decentralized cross-chain transaction scene, and credible access and identity revocation of the user are supported.

The invention discloses a real-name system information management method supporting multi-level authentication, and the method comprises the following steps: collecting basic identity information of a user, and storing the basic identity information through an asymmetric encryption algorithm; according to the use demand and the access authority requirement of the user, generating a multi-level authentication hierarchy; dividing the real-name system information into a basic information area, an authority information area and a sensitive information area according to the sensitivity of the real-name system information; carrying out distributed storage on real-name system information, and carrying out hierarchical encryption on data of different information areas by using a hierarchical encryption strategy; based on a multi-level authentication result and in combination with an access control strategy, authority distribution is carried out on the user, and controlled access of real-name system information is carried out under multi-dimensional verification; user information operation behaviors are monitored in real time, user behavior characteristics are analyzed based on an anomaly detection model, and when risk behaviors are recognized, an additional verification process is triggered or user operation is directly limited. According to the invention, safer, more flexible and more efficient real-name system information management is realized.

The invention relates to a carbon footprint management method and system of a lithium battery, electronic equipment and a storage medium, and belongs to the technical field of carbon footprint management, and the method comprises the steps: obtaining first carbon footprint data of each link of the whole life cycle of the lithium battery; the first carbon footprint data comprises energy used in each link, materials input and output in each link, wastes generated in each link, metering equipment of the energy material wastes, process equipment used in each link, basic information of the process equipment, carbon emission factors of each link, test equipment of the carbon emission factors, a test environment and a test method; carbon emissions of all links and a calculation method of the carbon emissions; generating a carbon footprint report according to the first carbon footprint data; and uploading the first carbon footprint data and the carbon footprint report to a block chain. According to the invention, block chain storage is carried out on the measurement information of each link, the carbon emission factor and the test / calculation process of the carbon emission, so that the credibility of the carbon footprint is ensured.

The invention relates to the technical field of data security, and redefines a block chain-based trusted data space management system and method, which comprises the steps of obtaining an initial credit result according to intelligent analysis of a block chain, creating an initial data credit module in a trusted data space, performing security grading on data to be encrypted in the initial data credit module, and storing the data to be encrypted in the trusted data space; executing different encryption strategies on the to-be-encrypted data according to the security level to encrypt the to-be-encrypted data; the storage module is used for storing the encrypted data needing to be chained to the block chain according to the computing power of the edge computing node; the access module is used for managing the authority of the user for accessing and applying data and policies needing to be accessed and releasing the corresponding access and application authority; and the matching module is used for releasing the access authority matched with the encrypted data to the user. The architecture of the trusted data space is established based on trusted computing 3.0, and the initial data credit module is distributed based on the block chain technology, so that the security and credibility of encrypted data are ensured.

The invention discloses a secret key issuing method, system and device, a storage medium and a program product, and relates to the technical field of information security, and the method comprises the steps: transmitting a verification public key certificate and a signature to a server through a WebSocket protocol at a client; receiving and verifying a first signature verification result returned by the server to obtain a second signature verification result; signing the random number in the second signature verification result to obtain a first signature value; and sending the first signature value and the random number to the server. After receiving the first signature value and the random number, the server generates a master key and a verification value, and issues the encrypted master key and verification value to the client; and the client decrypts and stores the master key. According to the scheme, bidirectional authentication is realized through an authentication mechanism of a public key certificate, and the credibility of both parties is ensured. And the random number is subjected to signature verification and signature, so that the replay attack is effectively prevented. In the secret key issuing process, the encryption certificate is used for encrypting the equipment information, the safety of the main secret key is ensured, and good expansibility is achieved.

The invention provides an aquatic product traceability management method and system based on a block chain, and relates to the technical field of aquatic product management, the aquatic product traceability management method based on the block chain comprises the following steps: establishing an aquatic product traceability network platform, and obtaining aquatic product full life cycle data in real time; performing anomaly verification on the acquired aquatic product full life cycle data based on a data verification method, and storing the verified data in an encrypted form in an aquatic product tracing network platform through a curve encryption algorithm; collecting feedback information after the user inquires the aquatic product traceability information through the aquatic product traceability network platform; and analyzing the collected user feedback information, and adjusting and optimizing aquatic product full life cycle management according to an analysis result. According to the method, the data is stored to the block chain in an encrypted form through a curve encryption algorithm, so that the security and non-tampering property of the data are ensured, and comprehensive optimization and guarantee are provided for production and management of aquatic products.

The invention discloses a maintenance accessory tracing method which is applied to a server. The method comprises the following steps: arranging circulation links of maintenance accessories according to an execution sequence, and obtaining original circulation information of the circulation links; a data block corresponding to the circulation link is generated according to the original circulation information, and a preorder data block hash value of the current data block is equal to a data block hash value of the preorder data block; a preorder data block hash value of a target data block corresponding to a first circulation link in the circulation links is a preset hash value; and calculating a data block hash value of each data block according to a preset algorithm, and constructing a hash link between the data block hash value of the preorder data block and the preorder data block hash value of the current data block to obtain a traceability chain. According to the invention, the completeness and non-tampering property of the maintenance accessory circulation information can be effectively ensured, and the transparency and reliability of maintenance accessory management are improved.

The invention discloses a secure startup method and system of a trusted controller, and belongs to the technical field of industrial control system security, and the method comprises the steps: configuring a secure startup strategy in U-Boot, and executing the secure startup strategy in the startup process of the trusted controller through a trusted controller drive; when the trusted controller is started, the security starting strategy is verified by adopting the first-level security strategy, and corresponding security check is executed according to the security starting strategy after verification is passed; after the trusted controller is started, the security starting strategy establishes a trusted chain according to the trusted files, measurement verification is carried out on all the trusted files of the trusted chain, and when all the trusted files pass verification, the trusted controller passes trusted verification; according to the secure starting method of the trusted controller, the reliability of the system is improved through establishment and verification of the trusted chain, a flexible protected area and comprehensive trusted file verification, and comprehensive security guarantee is provided for the system.

The invention relates to the technical field of employment management, in particular to a flexible employment management system based on a block chain and big data and a skill evaluation method. According to the invention, through autonomic skill label selection of the user and intelligent skill index generation, recommendation and matching are more accurately carried out on service supply and demand parties; according to the technical scheme, skill authentication information of a user is linked through the block chain technology, the skill authentication information comprises skill certificates and training experiences, the key problems of information asymmetry, non-transparent evaluation, low matching efficiency, insufficient right and interest guarantee and the like in a traditional system are effectively solved through combination of the block chain technology and the big data technology, and the user experience is improved. According to the flexible employment management system, a complete and coherent closed loop is formed from skill authentication to matching recommendation to right and interest guarantee and occupational development, the efficiency and fairness of a flexible employment market are greatly improved, and the sense of trust and the degree of participation of users are enhanced.

The invention discloses a medical health data analysis method based on privacy protection and information security, and relates to the technical field of health management, and the method comprises the steps: forming a data security management mechanism; obtaining corrected health data; analyzing and correcting the health data to form a disease distribution coefficient; predicting and forming a disease development trend based on the disease distribution coefficient; key preventive diseases are selected, and outbreak time points of the key preventive diseases are formed; analyzing to obtain a coping database of key preventive diseases; and the key preventive diseases are prevented in advance by using the data in the coping database. By correcting the abnormal value of the health data, forming a data security management mechanism and forming an outbreak time point for key disease prevention, abnormal data can be found in time, encryption can be carried out by using algorithms with different complexity degrees according to different privacy requirements of the data, excessive encryption is avoided, and the security of the health data is improved. And the more accurate outbreak time prediction can be carried out on the possible outbreak diseases.

The invention discloses a federal learning poisoning attack detection method based on gradient credibility. The method comprises the following steps: a client performs model training on an image data set under a federated learning framework, and sends a training result to a verification party and a server after training is completed; the verification party verifies the local model, summarizes verification results and sends the verification results to the server, and the server selects the optimal gradient and the most harmful gradient in the current round according to the verification results and stores the optimal gradient and the most harmful gradient in the server; meanwhile, the server calculates the credibility of the local gradient, malicious clients are filtered based on the credibility, the credibility is processed to serve as an aggregation weight during aggregation, and a credible global model is obtained through aggregation. The method can effectively identify malicious client poisoning attacks, and solves the problems that the detection effect is reduced when the number of malicious clients is greater than 50% in a traditional detection method, and the detection effect is unstable under different data sets and attack methods.

The invention discloses a regional target and environment dynamic sensing method for construction site video monitoring, and the method comprises the steps: carrying out the initial deployment of distributed cameras for a construction site, and carrying out the deployment optimization; collecting video data based on Kafka Broker cluster multithreading, collecting environmental parameters, and performing fusion based on Mahalanobis distance to obtain fused environmental parameters; performing multi-target detection on the collected video data, and analyzing behavior characteristics of the collected video data to obtain video target data; environment parameter feature representation is extracted from the fused environment parameters, multi-modal dynamic fusion is carried out on the environment parameter feature representation and video target data based on learnable parameters, and a comprehensive situation is analyzed through a situation awareness model to obtain real-time comprehensive situation data; and performing real-time risk assessment on personnel behaviors and environmental conditions in the construction site by adopting Bayesian network analysis based on the real-time comprehensive situation data, identifying risk events, and automatically generating alarm information. According to the invention, the intelligent level of construction site video monitoring is obviously improved.

The invention discloses an industrial wireless network trusted scheduling method and device based on a dynamic block chain, and relates to the technical field of transmission scheduling in the industrial internet, and the method comprises the steps: constructing an industrial wireless network system based on a dynamic block chain mechanism; on the basis of preset constraint conditions corresponding to the scheduling stage and the consensus stage, model construction is carried out with the purpose of maximizing the task trusted processing efficiency, an optimization model is obtained, and the optimization model carries all parameters to be optimized; performing model reconstruction on the optimization model based on a preset multi-agent Markov decision process model to obtain a target optimization model; and optimizing the target optimization model by adopting a preset rotation multi-agent deep reinforcement learning algorithm model on the basis of observation information of each industrial device in the industrial wireless network system, which is acquired in real time, so as to obtain a target parameter value corresponding to each to-be-optimized parameter. According to the method provided by the invention, the trusted processing efficiency of the tasks in the industrial wireless network system is improved.

The invention discloses a deep-sea operation performance evaluation method and device based on simulation deduction data, and relates to the technical field of ocean engineering and performance evaluation, and the method comprises the steps: deducing a deep-sea operation task completed by a deep-sea operation system based on a simulation deduction platform, and obtaining the simulation deduction data; obtaining an availability vector, a credibility vector and a capability vector evaluated before the deep sea operation system executes the operation task; obtaining a correction value based on the simulation deduction data; and based on the correction value and the operation performance evaluation formula, obtaining the operation performance output by the operation performance evaluation formula. The method is used for realizing accurate evaluation of the operation efficiency of the deep-sea operation system in the deep-sea characteristic operation scene.

The invention relates to the technical field of life cycle traceability, in particular to a full life cycle traceability system and method based on intelligent washing. The method comprises the following steps: acquiring washing clothes and user information, generating an RFID identification code, binding the RFID identification code with the user information, creating a user-clothes binding relationship, performing digital mirror image copying on the binding relationship, generating a clothes data file in combination with a database chain technology, and predicting the service life of the clothes by analyzing clothes state data and predicting the service life of the clothes. And making a personalized washing plan. And executing the washing plan and monitoring the washing result, and finally updating the clothes data file according to the washing effect to generate a washing traceability file. According to the invention, safer and more accurate full-life-cycle traceability operation is realized.

The invention provides a power load management simulation system, method and device and a medium. The power load management simulation system comprises a digital simulator, hardware and simulation software under a unified specification standard. The hardware comprises a calculation unit, an actual physical device and a simulation interface under a unified specification standard; the simulation software is used for providing a digital model and a simulation environment required by simulation; the calculation unit is used for acquiring the operation data of the actual physical device according to the digital model and processing the data; the digital simulator is used for performing power load management simulation on the processed operation data in combination with a digital model; the simulation system provides hardware and simulation software which are unified in specification and standard, compatibility and stability of the system can be guaranteed, integration complexity is reduced, and real-time performance and accuracy of simulation results are improved. In the simulation method, a simulation link sequence and an implementation method of each link under a standard are provided, so that the correctness and credibility of a power load management simulation result are ensured.

The invention discloses an Internet of Things digital information secure transmission method, and relates to the technical field of digital information transmission, and the method comprises the steps: firstly constructing virtual mapping and generating a prediction path through a sending end twin platform, and dynamically adjusting a transmission path in combination with state data collected by Internet of Things equipment in real time to adapt to a complex and changeable environment; secondly, a quantum communication link is adopted to generate a dynamic key, and the randomness and inseparability of a quantum state are utilized to ensure the security of the key and the data integrity; besides, a receiving end feeds back transmission time consumption, decryption time delay and a channel state to a sending end, and a twin platform of the sending end dynamically optimizes key distribution parameters and path prediction logic based on feedback information, so that a real-time self-adaptive mechanism is formed and can adapt to a continuously changing network environment; and finally, by dynamically optimizing the path weight matrix, resource waste is remarkably reduced, and the utilization efficiency of link resources is improved.

The invention relates to the technical field of mine management and control, and particularly discloses an intelligent mine management and control optimization method based on digital twinning. By monitoring and analyzing the geological condition, the microseismic influence, the slope form and the support instability of the monitoring area where the target mine slope is located corresponding to the current monitoring time period and calculating the deformation degree evaluation coefficient of the monitoring area where the target mine slope is located corresponding to the current monitoring time period, the deformation condition of the target mine slope is visually displayed. The problems of complexity, time consumption, labor consumption and the like of periodic patrol and measurement of mine management personnel are effectively solved, subjective errors of mine slope deformation analysis are reduced to a certain extent, the accuracy, reliability and rationality of a mine slope deformation analysis result are ensured, and meanwhile, the mining safety of the mine personnel is effectively ensured.

The invention relates to a cross-domain information interaction method based on a block chain cross-chain communication structure, and belongs to the technical field of information interaction. According to the method, messenger nodes are arranged on alliance chains maintained by two parties needing interaction, and a signature verification method based on Fiat-Shamir transformation and an elliptic curve integrated encryption scheme is combined, so that cross-domain identity authentication and message transmission are realized. The messenger node is used as a light node and only participates in cross-chain communication, so that the intra-chain communication efficiency is prevented from being influenced. The elliptic curve integrated encryption scheme provides a shorter key length and a faster calculation speed, optimizes network resources, and improves transaction processing efficiency. The method has security, high efficiency and expandability, is suitable for scenes in which different service providers use independent servers or block chain platforms to maintain intra-domain communication and want to perform cross-domain communication, and provides a new solution for cross-domain information interaction.