77 results about "Black list" patented technology

The invention discloses a self-adaptive intelligent current limiting and managing method, and relates to the technical field of current limiting. Comprising the steps of collecting real-time current data, historical current data and a system load state of a node, performing feature extraction on the real-time current data and the historical current data of the node, performing analysis and prediction on the collected current data by using an intelligent algorithm, and predicting current according to a current state analysis result; performing risk assessment on the current state in combination with historical current data of the node and a system load condition, analyzing predicted current data, and judging whether the current state has a short circuit risk or not; according to a short-circuit risk judgment result, determining a short-circuit risk node, selecting a current limit strategy, and adjusting current limit by setting a current limit protection value; and continuously monitoring the current state of the short-circuit risk node, adding the node which frequently causes an abnormal state into a blacklist, and carrying out key monitoring or regular maintenance.

The invention discloses a software process control and monitoring method and device and electronic equipment. The process information is collected, the management and control strategy is generated and applied to the target client, and a simple and convenient mode is provided for setting the black list and the white list of the process, so that the complexity of manual operation can be reduced, the threshold for configuring the white list is reduced, the management efficiency is improved, and the user experience is improved. And it is ensured that only the software process conforming to the management and control strategy runs on the target client, so that management and control and monitoring of software not conforming to the current application scene are realized. Besides, main running processes are collected to determine black and white lists, and the collected processes are filtered, so that the interference is reduced while the consumption of time and performance during data acquisition is reduced; during matching, according to comprehensive consideration of process names, paths, file attributes and the like, misjudgment is reduced, and the difficulty of disguising as a white list is increased.

The invention discloses a cross-network data security exchange method and device based on multi-layer protection. The method comprises the steps that multiple layers comprise a physical layer, a transmission layer, an application layer and a strategy layer; the physical layer adopts a one-way transmission optical shutter as a physical isolation means, the transmission layer adopts a hybrid encryption strategy combining asymmetric encryption and symmetric encryption, and the application layer is used for processing authority control, flow control, interface control, type control and sensitive data desensitization. The strategy layer guarantees the security of data exchange based on a bastion host, a black list, a white list and a log auditing mechanism; and the cross-network data security exchange method with multi-layer protection comprises a process of exchanging data from a non-security side to a security side and a process of requesting data from the non-security side to the security side. According to the scheme, comprehensive protection is provided for communication between networks with different security levels, and a feasible technical path is provided for constructing an open and highly controlled data exchange platform.

The invention belongs to the technical field of nuclear power plants, and particularly relates to a nuclear power plant equipment isolation lock management and control system and method. Comprising an isolation task module, an isolation authorization module, an isolation implementation module, an isolation sharing module, an equipment asset module, an emergency unlocking module and a data analysis module. The intelligent lock has the beneficial effects that the switching function of the intelligent lock is controlled through consistency verification and instructions, the problems that mistaken intervals, isolation and radiation boundaries are prone to being damaged are solved, field operation is standardized, a production closed loop is constructed, and therefore potential safety hazards and risks are reduced; the unlocking range and time are set according to the authority and the operation content, the past extensive and manual management mode is upgraded into intensive and electronic management, dynamic secret key anti-copying and anti-technical unlocking, a blacklist function is used for preventing key loss, and the safety production responsibility is forcibly implemented by means of an intelligent lock management and control system.

An autonomous mapping system defines the probing behavior of a mobile robot in a physical environment according to a multi-objective optimization. Through multi-target optimization, the detection behavior of the robot depends on a joint consideration of two or more detection targets, such as speed, coverage, and consistency. In at least one embodiment, the autonomous mapping system is customizable by a user through a user interface that allows the user to prioritize and / or select probe targets considered in multi-target optimization. The autonomous mapping system in one or more embodiments combines a favorable planning manner, for example, loop closure prediction for consistent mapping, kinematic dynamic prioritization for smooth trajectory generation, local refinement for improving mapping coverage, a time-based blacklist table for managing detection targets, a 2D attraction layer and recovery behavior for efficient path planning, and the like. And a recommendation system enabling an operator / user to refine subsequent probing operations, in particular for re-mapping.

The invention relates to a non-member customer loss prevention method and system based on payment opening and face recognition, and the method comprises the steps: obtaining the payment opening, a face image and dynamic behavior data of a non-member customer in real time, and enabling the dynamic behavior data to comprise a shopping path, standing time and moving speed; performing preliminary analysis on the dynamic behavior data by using an embedded edge computing device, identifying abnormal customer behaviors, and generating a preliminary risk assessment result; based on the preliminary risk assessment result, the payment openid, the face image and the dynamic behavior data are sent to a data center for secondary verification, and a verification result is generated; and if the verification result shows that the customer is matched with the blacklist or has an abnormal behavior, triggering an alarm and refusing the transaction, recording transaction information, customer characteristics and identification time, and generating and storing a transaction report. The method has the effect of improving the accuracy of the loss prevention system.

The invention discloses an industry large model content security capability construction method and device, equipment and a medium, and relates to the technical field of computers. Comprising the following steps: executing an embedded coding operation on knowledge base entries in a safe knowledge base through a bidirectional encoder model to obtain vector data containing original text literal meaning and semantic features of the knowledge base entries, and storing the vector data in a preset vector database; creating a blacklist library and a white list library based on a regular matching technology, and judging a risk level of a user input problem based on data stored in the blacklist library and the white list library; and selecting a corresponding answering mode based on the risk level of the question input by the user. Therefore, on the premise that user interaction experience is not affected, hint word attacks can be accurately recognized and intercepted, and it is ensured that large model generation content is safe and reliable.

The invention relates to the technical field of artificial intelligence, and discloses a method and a system for realizing multi-round questions and answers under security consultation based on a large model, and the method comprises the steps: receiving security consultation data of a target user to generate a dynamic user portrait of the target user, analyzing a first-level intention label and a first-level intention confidence coefficient of the security consultation data, and generating a second-level intention confidence coefficient; determining a second-level intention label of the target user; outputting structured query parameters of the target user; outputting dual-channel data of the security consultation data, and identifying a keyword blacklist, implicit commitments and undisclosed risks of the dual-channel data to filter the dual-channel data to obtain filtered multi-modal knowledge fragments; and generating a multi-dimensional answer of the target user to generate a multi-strategy model and a multi-strategy adjustment parameter and a user portrait update parameter of the dynamic user portrait, and executing multi-round questions and answers of the target user based on the multi-strategy adjustment parameter and the user portrait update parameter. According to the invention, the suggestion accuracy and personalization under security consultation can be improved.

The invention discloses a printer consumable management method and system, electronic equipment and a storage medium, and relates to the field of printer management. In the method, a first RFID of the consumable is read through an RFID reader of a printer, and the first RFID is transmitted to an application program through wireless transmission; when the application program receives the first RFID, querying a corresponding template through the first RFID and displaying the template in the application program; in response to the operation that a user clicks the target template, the target template is used for printing, the first length of each time of printing of the consumables is recorded, the multiple first lengths are added to obtain a second length, and the difference value between the total length of the consumables and the second length is calculated; when the difference value is smaller than the threshold value, it is prompted that the remaining length of the consumables is insufficient, and when the difference value is zero, the first RFID is added into the blacklist, and replacement of the consumables is prompted. By implementing the technical scheme provided by the invention, the use condition of the consumables can be monitored in real time, and the printer consumables can be effectively managed.

The invention discloses a method and system for reducing the outbound complaint rate, and the method comprises the steps: (1), selecting an outbound number according to the priority of customer attribution, provincial meeting, in-province and business city in a pre-call stage, firstly filtering the number marked as promotion / fraud, and then taking the number with the highest historical call completing rate; determining whether to call out or not according to historical complaint portraits of clients, business blacklists and a seven-day dynamic frequency algorithm; (2) an in-speech stage: collecting speech in real time, fusing and judging complaint risks by utilizing four-dimensional acoustic features and a BERT semantic model finely adjusted by an outbound corpus, and automatically hanging up once a risk index is greater than or equal to 160; and (3) in a post-conversation stage, performing double scoring on conversation texts and acoustic features, if the total score is greater than or equal to 70, writing clients into a blacklist, setting a 180-day cold and quiet period, and automatically removing complaints without newly added complaints at the end of the period. According to the method, the call-out mode of processing before and after calls is adopted, the risk judgment model and the AI technology are fully utilized, the complaint risk is successfully reduced, and the cost is saved.

The application discloses a hot ticket card blacklist generation method and device and a medium, relates to the technical field of computers, and comprises the following steps: determining a quantity threshold of a hot ticket card blacklist; sorting each initial ticket card according to the time attribute of each initial ticket card to obtain a first sorting result, and screening a first candidate ticket card from the first sorting result; if the first ticket card quantity of the first candidate ticket card is not less than the quantity threshold, determining a target ticket card from the first candidate ticket card according to a priority rule; if the first ticket card quantity is less than the quantity threshold, sorting each initial ticket card according to the balance information in each initial ticket card to obtain a second sorting result, and screening a second candidate ticket card from the second sorting result; screening the target ticket card from the first candidate ticket card and the second candidate ticket card, and taking the target ticket card as the hot ticket card blacklist. The application can accurately obtain a hot ticket card blacklist with higher activity, and can reduce the memory resource demand on the memory database of a gate.

The embodiment of the invention discloses an article circulation alarm information generation method and device, electronic equipment and a readable medium. A specific embodiment of the method comprises the following steps: in response to received missed scanning prompt information of unmarked personnel, obtaining a missed scanning personnel video frame sequence and article information, and executing the following generation steps: obtaining a personnel feature vector data set; pedestrian re-identification processing is carried out on the video frame sequence of the scanning-missing persons to obtain human body feature vector information of the scanning-missing persons; performing matching and binding processing on the human body feature vector information of the missing scanning personnel to obtain information of the missing scanning personnel; adding the scanning missing person information to a preset blacklist library; acquiring a person face image of the visited authorized user; performing facial feature extraction processing on the person facial image to obtain facial feature vector information; generating risk level information; and generating alarm information and sending the alarm information to a preset receiving end. According to the embodiment, the user experience is improved.

The present application provides an information processing method, apparatus, device, and storage medium, relating to the field of computer technology. The information processing method comprises: obtaining a data set to be processed, generating a relationship graph based on the data set; obtaining the characteristics of each node in the relationship graph and the characteristic value corresponding to the characteristic of each node, wherein the characteristic of each node corresponds to a target characteristic in a pre-trained decision tree model, and the decision tree model includes multiple tree nodes, and the tree nodes correspond to the target characteristics one-to-one; inputting the characteristic value corresponding to the characteristic of each node into the pre-trained decision tree model for decision processing, and obtaining the blacklist ratio corresponding to each node; and determining the risk level of the object corresponding to each node based on the blacklist ratio corresponding to each node. The present application can greatly improve the efficiency of screening and ensure the accuracy of the screening results.

The invention discloses a list matching method and device, electronic equipment and a computer program product. The method comprises the steps that data to be matched are obtained, and the data to be matched comprise attribute values to be matched corresponding to a plurality of attribute items respectively; the to-be-matched attribute values are matched layer by layer in multiple matching layers of a preset list Hash tree to obtain a matching result, the to-be-matched nodes are attribute nodes used for being matched with the to-be-matched attribute values in the preset list Hash tree, and the matching result is used for representing whether a path exists in the preset list Hash tree or not; under the condition that the matching result shows that the access exists in the preset list hash tree, it is determined that the to-be-matched data conforms to rules recorded in a preset list, the preset list is used for establishing the preset list hash tree, the preset list comprises multiple rules, and each rule comprises preset attribute values corresponding to multiple attribute items. The technical problem that the matching efficiency of the multi-attribute black list and the multi-attribute white list is poor is solved.

The embodiment of the invention provides a digital key access authentication method and device, terminal equipment and a storage medium. According to the method, a digital key is generated through a cloud end, key certification information is generated at the same time, when a vehicle machine end receives a digital key access request of an equipment end, if it is judged that the digital key is not an accessed effective key, the vehicle machine end requests the equipment end to provide the key certification information, and the digital key is verified according to the key certification information; and after the verification is passed, notifying the equipment end to delete the locally stored key certification information. Compared with the prior art that the in-vehicle terminal cannot intercept the vehicle use permission of the key which does not fail in time, by adding the key first access verification mechanism, the deleted key can be effectively prevented from obtaining the vehicle use permission again, the safety of the vehicle is improved, and compared with a blacklist mechanism, more storage resources do not need to be occupied.

The application relates to the technical field of software development, in particular to a non-invasive dynamic burying point system for an application, an implementation method and a storage medium. A starting class is defined for a burying point application, the starting class is connected to a process after the burying point application is started, and a transformer module encapsulated into a java agent is loaded. Compared with an existing annotation-based invasive burying point scheme and a static instrumentation burying point scheme, the application is effective for any jvm application, meanwhile, targeted burying point optimization of common framework and tool class libraries and progressive burying point processing of specific scenes are considered; a classification process is generally mainly aimed at methods of the application itself, and existing classification can be generally adopted for widely used library classes. When the application needs to change or cancel burying point logic, only the black and white list classification and the processor associated with the white list need to be changed, and the server side is re-calculated according to the black list to obtain the bloom filter parameter, so that the operation is simple, the burying point is flexible, and the application is not aware of the burying point.

The invention discloses a digital logistics-based cargo owner transport capacity pool access method, system and device, and the method comprises the steps: obtaining a target cargo type and a set transport score of a target cargo owner in response to a transport capacity reserve signal; obtaining a conventional cargo type and a transportation score of a transportation driver; judging whether a transportation driver exists in the blacklist of the target cargo owner or not, and obtaining a first judgment result; if the first judgment result is no, judging whether the transportation score is not greater than a set transportation score, and obtaining a second judgment result; if the second judgment result is no, judging whether the matching value of the conventional cargo type of the transportation driver and the target cargo type is not greater than a first set threshold value or not, and obtaining a third judgment result; if the third judgment result is negative, sending the business card information of the transportation driver and the transportation capacity recommendation request to the target cargo owner terminal; and if the first judgment result, the second judgment result or the third judgment result is yes, cancelling the recommendation of the transportation driver. According to the invention, a scheme can be provided for cargo owners to expand transport capacity resources.

The invention relates to the technical field of computers, in particular to a Java back-end log real-time analysis and abnormity early warning system and method.The system comprises a plurality of modules for cooperative work: a log collection module obtains and structuralizes Java application log data in real time and stores the data in a distributed system; the trend analysis module constructs a trend chart based on a time sequence; the threshold management module dynamically calculates early warning, abnormal and serious abnormal thresholds of each interface; the anomaly detection module determines an anomaly level by comparing the trend change value and the ratio with a threshold value; the feature management module extracts abnormal log feature values and compares the abnormal log feature values with a blacklist library to filter false alarms; the alarm notification module executes graded alarm according to the abnormal grade and the preset authority, and collects and feeds back to the optimization system; according to the system, through multi-dimensional trend analysis and dynamic threshold management, the false alarm rate and the missing report rate are effectively reduced, the anomaly detection accuracy is improved, and stable operation of a Java back-end application is guaranteed.

The invention discloses a software uninstalling method and device of a Windows operating system, a storage medium and a terminal, relates to the technical field of software engineering, and mainly aims to solve the problem of low software uninstalling efficiency under the existing Windows operating system. The method mainly comprises the following steps: monitoring a system event in real time to capture process event information of a software installation process; in response to a process ending event of the software installation process, performing multi-dimensional feature matching on the process event information and software matching information of blacklist software, so as to take the installed software as target software under the condition of the installed software corresponding to the process event information; and performing reverse cleaning operation on the target software according to the software matching information and the process event information of the target software so as to unload the target software. The method is mainly used for automatically uninstalling software.

The invention provides an information system red-black list intelligent evaluation method and system based on multi-dimensional data. The method comprises the following steps: acquiring data, namely acquiring multi-dimensional data including performance indexes, log data, user behavior data and business data from a target information system in real time; preprocessing the data, and cleaning the collected multi-dimensional data, including abnormal value processing, missing value completion and data standardization; feature engineering is carried out, evaluation features are extracted and screened from the preprocessed data, and feature weights are dynamically distributed based on business scenes; performing intelligent model evaluation, classifying the information system by utilizing a trained machine learning classification model and combining the dynamically distributed feature weight, and outputting a red list representing a high-performance system and a black list representing a low-efficiency system; and optimization execution: according to the red list and the black list, automatically triggering optimization processing for the black list. According to the method, comprehensiveness, dynamic self-adaptability and automation of the evaluation process are realized.

The invention relates to the technical field of artificial intelligence, can be applied to the fields of financial science and technology and medical health, and discloses an anti-fraud method, device, equipment and medium based on voiceprint recognition, and the method comprises the steps: obtaining a call voice signal, and processing the call voice signal to obtain a multi-dimensional voiceprint feature; inputting the multi-dimensional voiceprint features into a deep learning model for optimization to obtain optimized voiceprint features; detecting whether voiceprint early warning conditions are met according to the optimized voiceprint features and a constructed voiceprint template library; and if the voiceprint early warning condition is met, performing fraud judgment through a decision tree algorithm according to the call voice signal, the optimized voiceprint feature and a fraud blacklist voiceprint library to obtain a fraud judgment result. And the anti-fraud accuracy is improved.

The invention provides an operation activity multi-account cheating identification method and system based on graph propagation. The method comprises the steps that a client side collects user behavior data and reports the data, a server side constructs a heterogeneous user relation graph based on the data and gives a cheating risk weight to an edge, the cheating probability is calculated by using a PageRank algorithm based on a seed blacklist user and is subjected to hierarchical disposal, and the client side dynamically adjusts operation activity interaction logic according to a hierarchical result; according to the system, the method is realized through cooperation of the client SDK module, the server graph construction and propagation module, the hierarchical decision module and the client anti-cheating execution module. According to the method, the defects that an existing supervision model is high in labeling cost, large in recognition delay and incapable of achieving front-end real-time intervention are effectively overcome, and the method is scientific, efficient and good in transverse transplantation capacity.

This invention discloses an intelligent generation method and apparatus for well logging acquisition construction design. The method includes: determining a matching template from a pre-established well logging acquisition construction design template library based on the well logging task category, well type, and well shape in the well logging acquisition task notification; using a well logging acquisition construction information knowledge graph based on a pre-established well logging team information library to screen qualified well logging teams that match the well logging task category, well type, and well shape in the notification and whose relevant information is not on a set blacklist; and using the knowledge graph to extract the information of qualified well logging teams required for the template from the well logging task notification and the well logging team information library, and filling this information into the template to generate the well logging acquisition construction design. This method enables intelligent requirements analysis for well logging acquisition construction design, improving the quality and timeliness of design preparation.

The invention provides a dynamic adaptive multilevel federated learning backdoor attack defense method, which comprises the following steps of: 1, feature extraction and clustering: extracting client model update features from cosine distance and normalized update energy dimensions, and clustering by using a DBSCAN algorithm; 2, model output classification: marking clients as possible malicious or benign clients according to model output; 3, dynamic weight aggregation: scoring the screened client model according to the classification statistics and the client aggregation result, and determining the weight of the client model in the global model according to the score; 4, directional rollback detoxification: after the global model is aggregated, analyzing the parameter update quantity of the client to identify abnormal update, and adaptively adjusting towards the direction of the initial model to eliminate the back door influence; and 5, self-adaption blacklist: quantifying historical malicious behaviors of the client through the scoring dictionary, and pre-filtering model parameters transmitted by the client in an aggregation preparation stage. According to the method, a multi-level defense system is constructed, and the confrontation adaptability and the security defense capability of the federal learning framework are remarkably improved.

The present invention is applicable to the field of sound recognition technology, and provides a method, system, device and storage medium for improving the accuracy of bird category recognition, obtaining bird sound or image data; obtaining recognition results based on a bird recognition model; filtering the recognition results based on a white list, a black list and a gray list to obtain processing measures; wherein the processing measures include: if the recognition result meets the white list, outputting the recognition result as a bird category; if the recognition result meets the black list, collecting the recognition results, and adding the recognition results to the training set of the recognition model; if the recognition result meets the gray list, introducing expert knowledge to confirm the recognition result, and adding the recognition result to the white list; this application improves the accuracy of bird sound recognition through the setting of white, black and gray lists, and iterates the model recognition capability in a targeted and rapid manner.

System that features: an accessory (104) with an authentication chip (106) containing data signed by means of a private verification key, wherein the data includes a unique identifier related to the accessory; and a device (102) comprising: a public verification key which forms a verification key pair with the private verification key, and an identifier list which is configured as a global blacklist of unique identifiers which is maintained at least partially outside the system, wherein the device (102) is configured to read the data from the authentication chip (106), compare the unique identifier with the identifier list and reject the accessory if the unique identifier is found in the identifier list (904).

The invention relates to the technical field of matrix multiplication, in particular to a sparse matrix-dense matrix multiplication acceleration system and method. The system comprises a sparse structure analyzer, a structure weighting scheduler, a plurality of PE rows and a runtime feedback controller. The sparse structure analyzer extracts features of each row of the sparse matrix and calculates a structure cost score; the structure weighting scheduler is combined with the PE row real-time load to distribute the PE row with the minimum comprehensive cost for the matrix row; executing scalar-vector multiply-accumulate by the PE array in parallel; and during operation, the feedback controller generates a blacklist bitmap and a splitting signal through performance monitoring, and dynamically adjusts task allocation. Parallel data reading and load balancing processing and calculation are carried out through a three-stage assembly line. According to the method, the calculation efficiency and the energy efficiency ratio of sparse-dense matrix multiplication are effectively improved, and then the data processing speed of the CPU / GPU is improved.

The invention discloses a financial business process management system and method, a storage medium and electronic equipment, and the method comprises the steps: building a product recommendation model based on a bank admission rule base; the dynamic allocation engine is used for allocating signing coordination personnel by adopting a multi-strategy rotation algorithm; the desensitization data reconciliation module supports fuzzy matching of various field combinations; the post-loan risk control platform integrates voucher auditing, channel risk grading and merchant blacklist linkage functions; the examination supervision module is used for realizing screen switching prevention monitoring and abnormal behavior detection; the activity management unit is used for completing closed-loop management of issuing and cancelling after verification of the immediate reduction money; the channel evaluation matrix is used for calculating a five-dimensional risk index including the expenditure rate deviation degree and reject ratio estimation; the input tracking system updates the bank approval progress in real time and synchronizes the bank approval progress to the business end; and the data center stores customer portraits, the approval knowledge base and third-party credit investigation data in a unified manner, and the financial business process management system greatly reduces account checking time consumption.

The system and method can assess the merchant risk level on a more continuous metric scale rather than a binary classification. This can produce a continuous risk score that is proportional to the likelihood that the merchant is risky, effectively solving the gray-shade problem encountered by traditional blacklist methods. The continuous risk score feature provides greater flexibility because it allows the payment network to make dynamic pricing decisions (known as interchange optimization) based on the merchant risk level. Using collective intelligence from transactions across payment networks, the system and method can assess the merchant risk level with high accuracy. The system and method may be particularly beneficial for small merchants with lower transaction volumes because even a few fraudulent transactions can easily place them in the high-risk merchant category. In addition, the system and method can help payment processing networks make better decisions on cross-border transactions.

The invention discloses a gate ticket checking method and device and a medium, and relates to the technical field of computers, and the method comprises the steps: determining a number threshold value of a hot ticket card blacklist; sorting the initial ticket cards according to the time attributes of the initial ticket cards to obtain a first sorting result, and screening out a first standby ticket card from the first sorting result; if the number of the first ticket cards of the first standby ticket cards is not smaller than a number threshold value, determining a target ticket card from the first standby ticket cards according to a priority rule; if the number of the first ticket cards is smaller than the number threshold value, sorting the initial ticket cards according to balance information in the initial ticket cards to obtain a second sorting result, and screening out a second standby ticket card from the second sorting result; and screening out a target ticket card from the first standby vote card and the second standby vote card, and taking the target ticket card as a hot ticket card blacklist. According to the method and the device, the hot ticket card blacklist with relatively high activeness can be accurately obtained, and the memory resource demand on the gate memory database can be reduced.