398 results about "Blacklist" patented technology

The invention provides a multi-tenant-based centralized authentication and authorization method, system, device and medium, and belongs to the technical field of security and identity management, and the system comprises a unified portal layer, an authentication layer, an authorization layer, a strategy center and an audit monitoring layer. The unified portal layer receives a user request, identifies and injects a tenant identifier, and executes WAF rule verification, JWT signature verification and Token blacklist check; the authentication layer performs user or client credential verification on different accessed identity sources, generates and issues a JWT, and monitors the life cycle of a token; the authorization layer extracts an authority statement in the JWT and a locally cached strategy snapshot; the strategy center provides centralized storage, version management and visual editing of multi-tenant strategies; through cooperative work of each layer, accurate identification, unified authentication, centralized strategy management and comprehensive audit monitoring of tenants are realized. And the security, the expandability and the management efficiency of the system are effectively improved.

The invention discloses a data processing method and system based on a business management platform, particularly relates to the technical field of advertisement putting business management, and is used for solving the problems of difficulty in abnormal attribution and low decision-making efficiency caused by dimension data isolation of an existing system. The method comprises the following steps: synchronously acquiring a channel dimension click rate and a contact dimension blacklist interception rate; when the channel click rate is abnormally reduced, extracting a blacklist interception log associated with the corresponding channel and a product dimension conversion rate; user behavior path topology distortion intensity and decision manifold compactness caused by a blacklist strategy are verified based on an interception log; when the distortion intensity exceeds a threshold value or the compactness is lower than a threshold value, backtracking an advertisement exposure user path of a corresponding channel product; analyzing time sequence association of blacklist interception nodes and product exposure nodes in the path, and generating a candidate root cause set; and detecting the product conversion rate fluctuation direction in the abnormal time period, thereby determining the root cause from the candidate set, and remarkably improving the operation decision-making efficiency and accuracy.

The exchange of resource allocation assistance information between a requester User Equipment (UE) and an assistant UE allows the requester to make better resource allocation decisions. The assistance information may include a blacklist, a whitelist, resource allocation information, a candidate resource set, and measurement information, for example. Both UEs may have an assistance configuration to assist in the exchange of resource allocation assistance information, that may be obtained from a third apparatus, such as a base station. The configuration may include information related to when to trigger assistance, identities of UEs, and types of assistance information, for example. The requester may, based on the assistance information received, modify a candidate resource set at a Medium Access Control (MAC) layer. The requester may, at the MAC layer, determine a configured sidelink grant for a selected destination using assistance information targeting this destination.

The invention provides a multi-level architecture-based cross-chain communication and privacy protection method, system and device, and a storage medium, and relates to the technical field of data processing, and the method comprises the steps that an application layer receives a cross-chain asset exchange request initiated by a user through a first block chain network, the request comprises source chain asset information, target chain asset information and a user identity identifier; the application layer executes KYC anti-money laundering verification based on the user identity identifier, and verifies whether a source chain asset address exists in a preset blacklist, so as to obtain a compliance verification passing result; and the protocol layer generates a cross-chain transaction proposal in response to a compliance verification passing result, and constructs a verifiable proof based on a zero-knowledge proof technology. According to the method, the natural contradiction between privacy protection and supervision compliance in a block chain cross-chain scene is solved.

The invention discloses a vulnerability information knowledge graph construction method and a vulnerability patch acquisition method, and belongs to the technical field of computer program detection. According to the method, the vulnerability information related to the current vulnerability is collected as much as possible through a vulnerability information collection method based on search and used for constructing the vulnerability information knowledge graph, and then one or more patch codes related to the current vulnerability are mined and submitted through a screening method based on a white list and a filtering method based on a black list. Finally, more patch code submission related to the current vulnerability is obtained through vulnerability repair code submission similarity analysis, the purpose of finding all vulnerability patches is achieved as much as possible, and finally a security patch code submission set of the vulnerability number is output. According to the method, the patch mining accuracy can be improved, meanwhile, the patch with the complete vulnerability can be efficiently mined under the conditions that single-code submission and multi-code submission exist in the vulnerability patch, and the limitation and defects of an existing vulnerability patch mining method are overcome.

The invention discloses a phishing mail detection method and system based on a large model, and relates to the technical field of network security, the system comprises a real-time detection system and an offline analysis system, and a mail content analysis module receives real-time mail data to form structured data; the detection rule center matches the structured data with a detection rule, directly intercepts a mail hitting a high-confidence blacklist rule, and transmits the structured data of a mail hitting a low-confidence blacklist rule into a phishing mail detection agent; the phishing mail detection agent sequentially performs mail header suspicious feature analysis, mail body semantic analysis, mail body structure analysis and attachment content analysis on the structured data to obtain a mail intention, a link and an attachment file; and performing corresponding analysis by combining a detection tool, and judging whether the mail is a phishing mail or not according to an analysis result. A large-model-driven phishing mail detection intelligent agent is utilized, and a detection path is dynamically planned to cope with endless phishing mail attack means.

The invention discloses a wireless ad hoc network secure communication method based on dynamic trust management, which comprises the following steps: setting initial trust values for all nodes, and detecting node interaction behaviors in real time; evaluating and dynamically adjusting a trust value according to a node interaction behavior; the source node communicates with the target node and interacts trust values of the nodes; in combination with a dynamic source routing protocol DSR, trust values of all nodes in the current path and a path average trust value are calculated; selecting a path meeting the dual trust threshold as a secure communication path; if the trust value of a certain node in the path is continuously lower than the threshold for three times, marking the node as a malicious node and adding the node into a blacklist for isolation; and if the trust value of the malicious node rises to be above the threshold value and lasts for 2 cycles, recovering the communication authority of the malicious node. According to the invention, the trust value can be adjusted according to the node interaction behavior, the secure communication path is screened, the malicious nodes are isolated, and the overall security of the network is improved.

The invention relates to an encrypted ransomware attack rapid detection method and system based on a semantic traceability graph, and the method comprises the steps: synchronously carrying out the high-speed detection and depth detection of a preprocessed mixed log stream, and obtaining a corresponding high-speed detection result and a corresponding depth detection result; wherein the priority of the high-speed detection result is greater than that of the depth detection result; the high-speed detection result is obtained by performing malicious command matching and blacklist keyword detection on the preprocessed mixed log stream; the depth detection result is related to a semantic traceability graph generated by using semantic information related to the encrypted ransomware attack behavior in the preprocessed mixed log stream; when the high-speed detection result is that the encrypted ransomware attack behavior exists, all detection is stopped, and an alarm is triggered; and under the condition that the high-speed detection result is that the encrypted ransomware attack behavior does not exist, continuing to execute deep detection so as to determine whether to trigger an alarm according to a deep detection result. The method can effectively improve the detection precision and reduce the detection hysteresis.

The invention discloses a kernel boot test method for enhancing startability and stability by using Ranconfig for an edge device, which comprises the following steps of: generating a random kernel configuration file by using a Ranconfig tool, carrying out compiling and startup test on the generated configuration file, repairing a non-startable configuration file by using a config-bias algorithm, and carrying out kernel boot test on the kernel configuration file by using the Ranconfig tool. Generating a configuration item difference set according to the difference between the minimum default configuration file and the to-be-repaired configuration file, iteratively positioning configuration items failed to start and recording the configuration items to a key configuration database; the repaired kernel is further subjected to a pressure test through a fuzzy test module, and a black list and a white list are generated in combination with equipment hardware resources, so that configuration items are optimized, and the test coverage rate is increased; according to the invention, the availability and the stability of the kernel boot test of the edge device are improved.

The invention provides a fraud-related application detection method and device based on flow behavior analysis, a medium and a program product, and the method comprises the steps: carrying out the deep packet detection analysis of the current network downloading flow, comparing an application sample obtained through analysis with a preset white list and a black list, and screening out a missed to-be-detected sample; running a to-be-tested sample in a sandbox environment, collecting an interface image, extracting text features, and inputting a fraud-related classification model to judge whether the application program is a fraud-related application program or not; the method comprises the following steps: performing deep packet detection analysis on current network use traffic, extracting multi-dimensional behavior characteristics such as a terminal identifier, an application use frequency and an active time period, performing coding and scaling processing to form a fraud-related feature vector, and inputting a random forest detection model to judge whether a terminal has a fraud-related application use behavior or not. According to the method, through complementary fusion of content feature and behavior feature detection links, full-process identification of fraud-related applications in downloading and using stages is realized, and the coverage rate, the accuracy rate and the real-time performance of fraud-related detection are improved.

The invention discloses a security protection system of communication equipment. According to the security protection system, an executable file directory is locked through a file system protection unit, a temporary file directory is scanned, configuration and sensitive files are encrypted, and key configuration files are locked; the network management login and operation protection unit is used for grading all accounts based on preset configuration permissions, limiting the number of login clients, executing a white list mechanism and recording login information; meanwhile, an access forbidding blacklist is periodically updated through the data center platform, and abnormity analysis is periodically carried out based on log information uploaded by communication equipment. Through linkage of file protection, login control and data center analysis, a'protection-monitoring-response 'closed loop is formed, and the fragmentation problem of a traditional scheme is solved. According to the invention, through a modular design and a collaborative mechanism, the comprehensive defense capability of the communication equipment to internal tampering, external attacks and unknown threats is remarkably improved, and the method can be widely applied to the technical field of data security.

A method for classifying a digital certificate as malicious or non-malicious includes receiving the digital certificate from a network source and extracting textual fields from the certificate. The extracted text is embedded into a high-dimensional vector using a pretrained transformer-based encoder. The resulting test vector is queried against a vector data structure populated with reference vectors derived from known benign and malicious certificates. A similarity search is performed to identify a set of nearest reference vectors. A classification decision is made based on the labels of the most similar / nearest neighbors, using a voting mechanism. If a given set or number of them are labeled as malicious, the certificate is classified as malicious. If not, it is classified as benign. The classification result may trigger a network security action, such as blacklisting the associated IP address or identifying a botnet command and control server. The system may use various embedding techniques, including concatenating subject and issuer fields or embedding individual certificate attributes separately.

A system and method for generating a virtual asset wallet address blacklist database based on a graph attention network (GAT) are disclosed. A GAT AI engine server is configured to train a GAT-based AI model using an index of a full node for each virtual asset pre-stored in an index database server, common transaction item information pre-stored in a virtual asset transaction analysis database server, and a main blacklist consisting of high-risk virtual asset wallet addresses pre-stored in a main blacklist server, to calculate GAT scores based on the trained AI model, to estimate high-risk virtual asset wallet addresses using the calculated GAT scores, and to generate a GAT blacklist consisting of the estimated high-risk virtual asset wallet addresses; and a GAT blacklist database server is configured to store the GAT blacklists generated by the GAT AI engine server.

The invention discloses an Android instant messaging method and system based on dynamic key management and privacy protection. The system comprises an equipment fingerprint key generation module used for extracting equipment hardware fingerprints and generating a unique master key through a Hash algorithm; the dynamic session key rotation module is used for dynamically deriving a session key based on a timestamp confusion mechanism and a preset triggering condition; the key verification and synchronization module is used for realizing key legality verification through two-factor verification and a server blacklist mechanism; and the privacy protection module is used for protecting user data privacy by adopting an end-to-end encryption and local storage encryption technology, so that the technical problems in the background technology are solved, and the technical effects of remarkably improving the communication security and the privacy protection level through equipment fingerprint binding, dynamic key rotation and a two-factor verification mechanism are realized.

A computer-implemented method of processing a blockchain transaction, wherein the method is performed by a receiving party and comprises: obtaining one or more probabilistic filters, wherein each probabilistic filter encodes one of i) one or more sets of whitelisted data items, or ii) one or more sets of blacklisted data items; obtaining a blockchain transaction, wherein the obtained blockchain transaction is associated with a candidate data item corresponding to i) one of the one or more sets of whitelisted data items, or ii) one on the one or more sets of blacklisted data items; and determining whether to process the obtained blockchain transaction based on whether the candidate data item is present in at least one of the one or more probabilistic filters.

Systems and computer-implemented methods for freezing or unfreezing digital assets on a blockchain. A freeze administration service may send a signed freeze request to mining nodes, which maintain two blacklists of digital asset identifiers: a pending blacklist and a consensus blacklist. The digital asset identifiers may be transaction outpoints in some cases. If accepted by the mining node, the transaction outpoints in the freeze request are added to the pending blacklist, which causes rejection of any transactions using those outpoints, but does not cause rejection of any new blocks that include transactions using those outpoints. If a consensus threshold of acceptances is reached based on hash power, the request becomes an order and the outpoints are added to the consensus blacklist, which causes rejection of any transaction or block containing a transaction using those outpoints.

The invention relates to an exit-entry certificate authenticity identification method and system based on two-dimensional code identification, and a medium. The method comprises the following steps: constructing a cross verification rule base comprising logical relationship information between two-dimensional code information of the entry-exit certificate and signing and issuing information of the entry-exit certificate; acquiring a data page image of an entry-exit certificate to be detected; identifying a two-dimensional code in the preprocessed data page image by using a two-dimensional code identification engine; identifying signing and issuing information in the preprocessed data page image; according to the dynamic two-dimensional code verification library, the dynamic blacklist library and the identified signing and issuing information, uniqueness verification and legality verification are carried out on the identified two-dimensional code information; comparing the corresponding relationship between the identified two-dimensional code information and the identified signing and issuing information according to a cross verification rule base; and judging the authenticity of the entry-exit certificate and generating a report. According to the invention, true and false identification is carried out through three dimensions, the identification accuracy is high, and high-risk false and false situations such as same codes, different certificates and tampering fields can be accurately identified.

The invention discloses an authentication filtering method, system and device and a storage medium. The method comprises the following steps: determining an authentication mode of an access and mobility management function; according to the authentication mode, configuring black and white list parameters required by authentication; receiving an authentication request of a target object; the authentication request carries a user identification code and a user address; and according to the black and white list parameters and the authentication request, based on an authentication filtering strategy, determining to reject the authentication request, or sending the authentication request to an authentication server function. Through authentication filtering, the authentication workload of the authentication server function is reduced, the network load is reduced, and the communication efficiency is improved. The method can be widely applied to the technical field of wireless communication.

The invention provides an IPSecVPN encrypted traffic security detection method based on an FPGA, and the method comprises the following steps: S1, hardware analysis, S2, model construction, S3, rule updating, S4, intelligent recognition, S5, hardware acceleration, S6, dynamic encryption, and S7, joint defense and joint control. Through combined training of supervised learning, unsupervised learning and semi-supervised learning, the connection Camp can be identified; the C server hides malicious scenes such as heartbeat packets and host networking environment anomalies, can also dynamically trigger strategies according to attack types, and meanwhile utilizes a special hardware assembly line in FPGA hardware to map CNN reasoning layer convolution kernel calculation into a parallel logic unit, after acceleration, rule matching engine SPI blacklist retrieval delay is shortened, packet length distribution histogram generation speed is increased, and data transmission efficiency is improved. Threat score calculation and flow feature extraction are synchronized.

The invention provides a log burying point collection method and system, and the method comprises the steps: determining a log data source, collecting log burying point data from the log data source, and storing the log burying point data in a source data storage module; regularly reading the log burying point data in the source data storage module based on a preset reading period, and performing blacklist filtering on the log burying point data to obtain an effective event set and an effective field set; when a new field exists in the effective field set, constructing a new field statement, and packaging and storing the new field statement to a metadata storage table of the field; when newly added events exist in the effective event set, table building statements are built, packaged and stored in a metadata storage table of the table; and executing the new field statement and / or the table building statement. According to the method and the device, the change of the engineering log can be automatically sensed, the log is deeply analyzed, key information is accurately extracted, and a highly adaptive data model is automatically constructed, so that the modeling efficiency, accuracy and adaptability are greatly improved.

The invention relates to the technical field of Internet of Vehicles information security, and discloses an Internet of Vehicles-oriented Beidou signal spoofing detection and mitigation intelligent system and method, and the system comprises a multi-dimensional data sensing and preprocessing module, a deep learning joint detection module, and a security mitigation and reputation management module. The method comprises the following steps: firstly, extracting a physical layer signal feature and a network flow stability feature and generating a multi-dimensional feature vector; secondly, performing feature compression and preliminary screening by using an auto-encoder, analyzing a time sequence evolution rule through a long-short-term memory network, and outputting a judgment probability; and finally, executing hierarchical defense according to the judgment probability, responding to local threats by dynamically adjusting a measurement noise covariance matrix or a hard isolation strategy, evaluating network node reputation based on a path damage index, and adding abnormal nodes into a dynamic blacklist. Through the multi-dimensional feature fusion and deep learning cascade architecture, the spoofing attack detection accuracy is improved, and the diffusion of false information in the Internet of Vehicles is effectively blocked.

The invention provides a malicious request interception system based on multi-dimensional behavior analysis and cloud-ground collaboration, relates to the technical field of network security, and analyzes normal equipment characteristics, a user behavior sequence and a cloud malicious equipment blacklist by collecting TCP / IP protocol stack characteristics and combining dynamic characteristics of the user behavior sequence. First interception is performed according to an analysis structure, deep identification is performed on a user behavior sequence after the first interception based on time sequence analysis and clustering analysis, and second interception is performed according to an identification result, so that the problems that a static rule cannot identify novel attacks and group attack features are difficult to capture are solved; and carrying out content verification on the user behavior sequence after the second interception, and carrying out third interception according to a verification result, thereby realizing dynamic adaptation of a service scene, solving the problem of poor static rule adaptability, carrying out whole system synchronization on all intercepted malicious logs, avoiding cross-node missed interception of malicious requests, and forming a defense iteration closed loop.

The invention relates to the technical field of artificial intelligence and the field of medical information security and financial services, in particular to a short message anti-fraud method and device based on artificial intelligence, equipment and a medium. According to the method, the to-be-sent short message is analyzed, the to-be-sent short message and the equipment information are subjected to feature classification extraction, for any feature category, the corresponding feature vector is evaluated according to the evaluation model, all evaluation results are fused, and the communication number is marked as the blacklist number. And receiving the short message of the communication number is blocked. The method can be applied to business scenes such as financial service and medical information security, the to-be-sent short message is analyzed by using the first anti-fraud model through the mobile terminal, if the short message is a problem short message and a user confirms sending, the short message is reported to the cloud, the result is evaluated and fused, and the global blacklist is updated to stop receiving the short message. Therefore, the short messages are comprehensively analyzed in the short message sending process of the mobile terminal, and the short messages meeting the conditions are accurately marked and blocked.

The invention provides an SQL (Structured Query Language) statement generation method and device and electronic equipment, and the method comprises the following steps: acquiring information input by a user, and retrieving the information input by the user based on a knowledge base generated by retrieval enhancement to obtain context information; preprocessing the information input by the user, and generating an SQL statement based on the preprocessed information and the context information; verifying the SQL statement based on a preset keyword black list, a table name white list and a mapping relationship between the fields and database fields; if the verification is passed, verifying whether the SQL statement is normally executed or not; and if the SQL statement is normally executed, performing complex calculation logic judgment, dynamic Python analysis and sandbox execution on the SQL statement, and determining a query result. The overall performance and practicability of the Text2SQL technology are effectively improved by enhancing the understanding ability of the model for complex queries and the accuracy of generating the SQL statements and ensuring the safety and compliance of generating the SQL statements at the same time.

A composite cryptographic data structure is described, and corresponding methods, systems, and computer readable media. The composite cryptographic data structure is instantiated based on an underlying set of cryptographic tokens (e.g., blockchain / distributed ledger tokens) that, in some embodiments, are transferrable through on-chain transactions established on one or more distributed ledger networks. Identity validation, in some embodiments, may occur at one of composite cryptographic data structure instantiation or composite cryptographic data structure redemption, or both, through the use of a whitelist or a blacklist data structure.

The invention provides a method and device for inhibiting a non-RedCap cell from improving access stability, and the method comprises the steps: loading a blacklist of UE, the UE currently resides in a first network, and the blacklist is used for storing redirected frequency points and PCIs which are not supported in a connection state of the first network; obtaining a target cell supporting a second network in response to a redirection instruction of the base station; determining whether to execute a redirection instruction based on whether the target cell exists in the blacklist; when redirection succeeds, the UE is connected to a second network of the target cell, when redirection fails, the PCI of the target cell is associated with a timer and then added to the blacklist, and the timer is used for setting the inhibition duration of the PCI of the target cell. According to the method and the device, the access abnormity occurring when the RedCap UE tries to access the non-RedCap cell is avoided, the stable access of the UE is ensured, the service continuity is ensured, and the power consumption loss is avoided.

A computer system extracts product data from a website and correlates product records from multiple sources to one another as corresponding to the same product. A website is crawled efficiently by rendering webpages using a virtual browser that ignores blacklisted elements, extracts data from objects without rendering, and suppressing retrieval of remote resources. Data is extracted according to engine control statements including a selector and extractor. A website may be crawled repeatedly and changes in extracted data may be detected and flagged. Engine control statements may be automatically changed in response to detecting a change in the configuration of the website. Images of product records may be correlated with one another by first comparing text of the product records and selecting images for comparison based on composition. Images are compared using a machine learning model. Images determined to be similar may be presented to a human for a correlation decision.

The invention relates to an equipment black and white list management method and device, a storage medium and electronic equipment. The method comprises the following steps: receiving feedback information input by a user, and identifying a feedback identifier, an equipment problem type and a user appeal in the feedback information; obtaining business data of the target equipment from a business background according to the feedback identifier, and inputting the feedback information and the business data into a target large model, so that the target large model executes semantic understanding and rule reasoning according to the feedback information and the business data in combination with a business knowledge base, and generates a black and white list change suggestion; processing the original blacklist and whitelist of the target device based on the blacklist and whitelist change suggestion, and generating a new blacklist and whitelist meeting user demands; and uploading the new black and white list to a cloud storage platform, and feeding back a processing result of the downloading link containing the new black and white list to the user. The technical problems that equipment capability identification depends on manual editing of black and white lists, the process is tedious and inefficient, and errors are prone to occurring are solved.

The invention discloses a voice response processing method and device, electronic equipment and a storage medium. The method comprises the following steps: determining a first voiceprint feature of first voice data, wherein the first voice data comprises voice data generated by executing a first voice interaction task in an interactive voice response stage; determining voiceprint blacklist information, wherein the voiceprint blacklist information comprises a plurality of second voiceprint features and semantic features associated with the second voiceprint features; and according to the first voiceprint feature and the voiceprint blacklist information, determining a task processing resource matched with the first voice interaction task from a plurality of task processing resources, and using the task processing resource to assist in processing the first voice interaction task continuously executed after the end of an interactive voice response stage. According to the scheme, the efficiency of solving the customer demands can be improved, and unnecessary interference or loss to a customer service center is avoided.

The application discloses an IP governance method based on SAVA suitable for a cloud native system and belongs to the technical field of network security, and is characterized in that the method comprises the following steps: S1, a virtual SAVA device is used to abstract the function of the SAVA device into a capability in the cloud native system; S2, the capability is combined into a micro-service chain; S3, in a false source identification stage of source address identification, a false source address is identified; S4, in a real source identification stage of source address identification, an existing real source identification function is abstracted into a capability, and real source identification is performed; S5, in a black and white list generation stage, an IP address black and white list is generated according to intelligence of source address identification; S6, the cloud native system blocks a black list IP address according to the generated IP address black and white list; and S7, finally, intelligence is shared. The application can break through the restriction of an existing network structure, realize IP address governance based on SAVA in the cloud native system, and improve efficiency and flexibility.