27 results about "Event tracing" patented technology

The invention relates to a transaction event interpretation system based on information traceability. The transaction event interpretation system comprises an architecture management module, a vector deployment module and a transaction recognition module, the architecture management module comprises an association construction unit and a type calibration unit; the vector deployment module comprises a transaction construction unit, a transaction evaluation unit, a vector generation unit and a vector deployment unit, and the transaction identification module comprises an information acquisition unit and a transaction index unit. According to the method, two dimensions of static configuration and dynamic retrieval are combined, firstly, static configuration of retrieval vectors is carried out on each monitoring point according to basic information, so that each monitoring point has target performance during transaction event tracing, on the other hand, the incidence relation between the monitoring points is taken into account, information isolation is avoided, and in addition, through dynamic configuration of the probe, the accuracy of transaction event tracing is improved. And according to the actual condition of each monitoring point, external data is rapidly obtained to complement the external event basis required by transaction event tracing.

The invention discloses a real-time traffic flow abnormal event tracing method and system based on edge calculation, and the method comprises the steps: obtaining traffic flow data of edge nodes, analyzing the dynamic impedance of a road segment according to the traffic flow data, calculating the path selection probability of each path through employing an abnormal event wave proportion, extracting a traffic flow abnormal road segment, and carrying out the tracing of the traffic flow abnormal event. And performing spatial overlapping analysis on the abnormal road sections according to the path selection probability, matching the traffic event announcement root cause and the meteorological early warning root cause based on the association strength of each abnormal road section, generating an optimal matching root cause through a maximum weight bisection matching algorithm, and tracing the upstream traffic flow by using the optimal matching root cause and the path selection probability. According to the method, dynamic impedance analysis, SIR propagation simulation and Shapley value are utilized to quantify the contribution degree of the root cause to the abnormal road section, full-link traceability of the root cause, the path and the upstream node is formed, relatively complete data support is provided for traffic abnormity diffusion caused by traffic abnormity and meteorological abnormity, and the practicability and decision value of a traceability result are improved.

The application discloses a Java-based distributed transaction management system and relates to the technical field of distributed systems. In view of the contradiction between transaction consistency and high concurrency and high availability in a distributed system, the scheme comprises the following: a transaction coordination module, which is used for constructing a cluster based on a Raft protocol to guarantee continuous availability of a service, realizing transaction full-life cycle management by relying on an extended state machine engine, and dynamically selecting an optimal communication path of a transaction according to scheduling decisions and a real-time network topology state; a local transaction management module, which is embedded in each microservice and is used for realizing local execution and state reporting of a transaction; a multi-level log module, which is used for realizing traceability of a transaction state and recovery of a fault through multi-level storage and event tracing; an intelligent scheduling module, which is used for realizing dynamic optimization of transaction processing based on an LSTM model and QoS indicators; and a monitoring and alarming module, which is used for collecting transaction full-link logs and performance indicators in real time and realizing full-link observability. The application is suitable for high-reliability and high-concurrency scenarios.

The invention relates to the field of constructional engineering informatization and intelligent safety management, discloses a construction safety dynamic management system and method based on BIM and RFID fusion, and aims to solve the technical problems of fuzzy identity recognition, inaccurate space positioning, delayed early warning response and difficult event tracing in traditional construction safety monitoring. Comprising an RFID sensing subsystem, a BIM data management subsystem, a space mapping and conflict detection subsystem, a grading early warning subsystem and an event tracing analysis subsystem, and realizes closed-loop management from sensing, mapping, early warning to tracing: centimeter-level real-time positioning of personnel and machinery is realized by deploying a multi-band RFID reader-writer array and an active tag; and when a space conflict is detected, a three-level early warning mechanism is triggered, and synchronous intervention is performed through three channels of sound and light, a mobile terminal and a large screen. By means of the technical scheme, the safety situation sensing precision and response speed of the construction site are remarkably improved, the early warning accuracy rate exceeds 98%, the accident rate is reduced by 70% or above, and whole-process data-driven decision making is supported.

The invention relates to a lightweight network flow storage and management method and system based on flow clustering, and belongs to the field of computer network security, and the method comprises the steps: deploying a Zeek monitoring component and P4 equipment at a network boundary and a core node, and carrying out the structural analysis of a multi-source weblog; based on data source and flow feature clustering and grading processing, dividing into a key flow, a common flow and a secondary flow; hierarchical forwarding and priority scheduling of the logs are realized through Filebeat and Kafka; a hierarchical storage architecture of a core flow layer, a main service flow layer and an archiving flow layer is constructed based on ClickHouse, and efficient retrieval and traceability analysis are realized through a materialized view and a multi-dimensional index. According to the invention, flexible scheduling and grading processing of traffic can be realized in a high-concurrency network environment, the overall throughput efficiency and security situation awareness capability of the system are improved, real-time performance and storage cost control are both considered, and the method is suitable for threat monitoring and event tracing scenes in a large-scale network environment.

An application-level determination of anomalies in response to issuance of an incident ticket / report. AI including NLP is implemented to decipher the unstructured freeform data in an incident ticket to positively identify the resource event that caused the incident. Once the resource event has been identified, a resource event tracing record associated with the resource event is analyzed to determine one or more anomalies. Analysis of the resource event tracing record may include comparison of the resource event tracing record to other resource event tracing records having one or more similar attributes to determine differences in recorded metrics, which may indicate anomalies. In response to determining the isolated and / or systemic anomalies, an anomaly report that indicates at least a portion of the determined anomalies is generated, and electronic communication is initiated.

This invention discloses a real-time control and management platform for intelligent well firing, relating to the field of well firing control technology. It solves the technical problems of traditional solutions lacking multi-hop communication control between nodes, failing to monitor relay node status in real time, and being unable to dynamically adjust strategies based on real-time data, thus affecting the control effect of the management platform on intelligent well firing. The platform divides the well firing distribution area into multiple zones, with each zone equipped with multi-hop relay nodes, forming a hierarchical transmission path. This solves the problem of limited single-hop communication distance, making it particularly suitable for complex terrains such as mountainous areas and underground environments, expanding coverage through relay hops. Simultaneously, a production mode configuration and full-dimensional status management module enables flexible configuration of production modes, status tracking and visualization of well firing equipment and the entire operation process, operation trajectory playback and event tracing, and quality control management of the firing process, providing comprehensive data support for intelligent firing decision-making and operation process control.

The embodiment of the application provides a kind of program performance bottleneck automatic analysis method and system, it is related to application research and development technical field.The method can respond to the program running instruction input by user, based on target program path, run target program, then according to monitoring parameter setting performance analysis tool data acquisition strategy, and in target program running process, according to data acquisition strategy, monitoring data is obtained from event tracking interface.After target program ends, based on analysis algorithm and monitoring data, calculate key performance parameters, then according to result output mode and key performance parameters, generate structured report.Data acquisition strategy includes the counting object of performance counter and process filtering rule.The method can automatically call event tracking interface to complete performance data acquisition and analysis by user specified analysis rule, and real-time output performance bottleneck analysis result, can reduce the complexity of program performance analysis operation, improve program performance analysis efficiency.

The invention relates to the technical field of natural language processing and text mining, and discloses a dynamic granularity timeline abstract generation method based on multi-agent collaboration and application thereof.The dynamic granularity timeline abstract generation method comprises the steps that firstly, a high-quality text set related to a query theme is screened out from a multi-source heterogeneous text through cooperative work of three kinds of agents including generation, debate and decision; then dynamically dividing the text into a specified number of semantic clusters through cooperation of another group of agents based on granularity parameters specified by a user; generating an event abstract for each cluster; and finally, carrying out fact consistency verification. According to the method, the accuracy and interpretability of information screening and event grouping are improved through a multi-agent debate mechanism, flexible dynamic control over abstract granularity is achieved by introducing granularity parameters, the content reliability is guaranteed through authenticity verification, the capacity of automatically generating reliable and customizable timeline abstracts from complex text streams is improved, and the method is suitable for popularization and application. The method is suitable for multiple scenes such as public opinion analysis, event traceability and decision support.

A method and system for determining, based on event tracing associated with user devices connected to a cellular network, locations of the user devices in indoor environments (hereinafter, indoor locations), for example in order to determine quality of service maps of (e.g., urbanized) indoor environments of a geographic area covered by the cellular network.

The invention belongs to but not limited to the technical field of data processing, and discloses a target positioning and event tracking visualization system and method based on a large language model, and the system comprises a user input processing module which receives unstructured natural language input from a user, extracts the intention of the user, and completes the scheduling of a downstream module and the initialization of a processing flow; the big language model event extraction module based on the RAG is used for fusing the retrieval enhancement generation framework and the big language model and automatically identifying and extracting structured event information from a natural language; the geographical name analysis and space positioning module is used for standardizing geographic information entities in a natural language and accurately mapping the geographic information entities into a geographic coordinate system so as to provide support for space positioning and visualization of subsequent events; the map service and event visual display module consists of two independent services which are respectively responsible for static service of a map tile layer and visual rendering of an event track; the method is used for event position labeling, track visualization and interactive map display.

Mechanisms are provided for generating a holistic view of an event processing pipeline of an event driven architecture. Curation of runtime information from components of an event processing pipeline is performed, where the runtime information comprises real-time runtime metrics, aggregated logs, event tracing / recording data structures, and configuration information. The curated runtime information is correlated to generate correlated runtime data. Predictive models and predictive analytics process the correlated runtime data to predict anomalies in the components of the event processing pipeline. A fault circuit interrupt machine (FCIM) processes the predicted anomalies based on user resiliency configurations to determine recommended event resiliency remediation actions for addressing the predicted anomalies. A real-time holistic view of the components of the event processing pipeline is generated based on the correlated runtime data, the predicted anomalies, and the determined recommended event resiliency remediation actions.

Mechanisms are provided for generating a holistic view of an event processing pipeline of an event driven architecture. Curation of runtime information from components of an event processing pipeline is performed, where the runtime information comprises real-time runtime metrics, aggregated logs, event tracing / recording data structures, and configuration information. The curated runtime information is correlated to generate correlated runtime data. Predictive models and predictive analytics process the correlated runtime data to predict anomalies in the components of the event processing pipeline. A fault circuit interrupt machine (FCIM) processes the predicted anomalies based on user resiliency configurations to determine recommended event resiliency remediation actions for addressing the predicted anomalies. A real-time holistic view of the components of the event processing pipeline is generated based on the correlated runtime data, the predicted anomalies, and the determined recommended event resiliency remediation actions.

The application discloses a system and method for distributed attack process forensics, introduces a user-unaware, distributed active defense model into attack forensics, automatically constructs a high-fidelity and high-density camouflage environment in a network, constructs decoys and luring traps along the way in the network and terminal, actively spreads false messages and polluted data to an attacker, and when the attacker intrudes, issues a forensics strategy and a forensics component in an Agentless mode, realizes distributed and non-invasive dynamic forensics through system kernel event tracking, and makes up for the shortcomings of existing attack forensics.

The invention provides a risk-driven industrial event credible traceability intelligent method, and relates to the technical field of intelligent event traceability, and the method comprises the steps: carrying out the event preliminary screening through risk perception, and obtaining the risk level of an event; an event identifier is obtained for the event, a deterministic index is established for the event through a layered weighted bloom filter, the layered weighted bloom filter comprises M sub-weighted bloom filters, M is the total number of the risk levels, and the jth sub-weighted bloom filter is endowed with a target false positive rate; obtaining a Hash abstract of an original data snapshot of the event, and obtaining a final root Hash corresponding to the event and a Hash value of an index state snapshot through a Merkel-Parene tree; and the layered weighted Bloom filter is optimized periodically. According to the invention, real-time indexing, risk perception and credible tracing of massive industrial events are realized.

This invention provides an AI-powered emotion monitoring, multi-member access control, and security incident tracing system and method, belonging to the fields of AI emotion recognition and multi-user home security management. The system includes: an AI emotion risk recognition module, which, with user authorization, collects only voice tone and text semantic features, uses local inference to identify high-risk emotions, and sets limits on collection duration and reporting frequency; a multi-scenario heartwarming intervention module, which desensitizes and reports high-risk emotions and automatically matches rescue entities, forming an intervention closed loop; a multi-member access control module, which automatically identifies roles in multiple scenarios, achieving hierarchical access control and self-adaptive differentiated security strategies; a full-scenario security incident collection module; and a desensitized tracing and evidence storage module. Under the premise of privacy compliance, this invention achieves accurate emotion recognition across all scenarios, fine-grained access control, rapid cross-entity rescue, and reliable incident tracing, forming a complete security closed loop of pre-event prevention, in-event intervention, and post-event tracing, applicable to various scenarios.

A computer system includes memory hardware configured to store structured microservice configuration data having multiple microservice entries each associated with one of multiple microservice applications of a request processing architecture. The system includes processor hardware configured to access structured microservice configuration data to identify the microservice applications of the request processing architecture, subscribing to messages transmitted by the identified microservice applications for event monitoring, and receiving multiple messages transmitted by the identified microservice applications. For each of the multiple received messages, the instructions include analyzing one or more fields of the received message to determine a correlation identifier associated with the received message, identifying one of the multiple request data structures, storing an event message entry in the identified request data structure, and transforming a user interface of a user device to display at least a portion of the multiple event message entries.

The invention relates to a security event tracing method and device based on a block chain, equipment, a storage medium and a computer program product. The method comprises the following steps: encrypting log data and storing the encrypted log data in a decentralized block chain network; integrating log data of a plurality of devices and / or a plurality of systems in the block chain network to generate a data view; according to the data view and the log data, safety inspection is executed for a safety event, and whether a safety problem exists or not is judged; in response to the detected security issues, determining a causal relationship between the patrolled security issues, and determining an attack source corresponding to the security issues; and log data in different block chain networks are integrated through a cross-chain technology, and tracing and response are performed on security events of different block chain networks in combination with a preset security event early warning mechanism of a block chain and a preset security event knowledge base based on the block chain. By adopting the method, the safety event patrol and processing efficiency can be improved.

The invention discloses a real scene mobile device storage performance self-adaptive evaluation method and device and a medium, and relates to the technical field of storage performance evaluation, and the method comprises the steps: connecting a mobile device through an ADB, and configuring an ftrace subsystem to start block layer I / O event tracking; performing I / O event collection for multiple times when real user operation of the target application is executed; after collection, pulling and analyzing the trace file to extract a plurality of performance indexes; performing quality diagnosis on the trace file and outputting rating; when the rating is qualified, historical baseline data matched with the current test scene information is obtained from a baseline database, and the matching is performed based on a scene identifier and a wildcard character mode; and on the basis of the extracted indexes and the matched base line, single scores of the indexes are calculated by adopting a piecewise linear scoring algorithm, a comprehensive health degree score is obtained after weighted fusion, and a performance grade is determined. The invention provides a mobile equipment storage performance evaluation scheme capable of realizing automation and multi-dimension and supporting cross-version performance comparative analysis based on a real application scene.

The invention discloses a data grid risk analysis system for event tracing. The system comprises a Web content acquisition module used for acquiring Web content from the World Wide Web; the analysis module is used for converting the Web content into a structured information unit containing a source content identifier and calculating an inherent information risk value of the structured information unit; the graph construction module is used for dynamically constructing an information traceability graph according to the structured information unit; and the infection risk analysis module is used for executing reverse tracing of the information spreading path on the information tracing graph. According to the method for extracting the source relation from the unstructured Web content and quantifying the risk, the technical problems of data foundation missing and logic chain breakage during tracing of infection risk information in the Web environment are solved, and reliable and efficient risk judgment tracing is achieved.

The invention discloses a network event tracing method and device, a storage medium and a program product, and the method comprises the steps: obtaining a known network event, and initializing a context and an associated node chain according to the known network event; one round or multiple rounds of iterative reasoning are carried out, each round of reasoning process comprises the steps that the context is analyzed, a database query statement is generated, and a database comprises interaction log data of multiple entities in a network within a preset duration; executing the database query statement to obtain a database query result, and generating candidate associated entities according to the database query result; selecting the candidate association entity to be added into the association node chain, and updating the context; and determining whether the reasoning process meets a preset termination condition or not, and when the preset termination condition is not met, carrying out the next reasoning process.

The embodiment of the invention provides a family event tracing method and device, electronic equipment and a storage medium, and relates to the technical field of the Internet of Things, and the method comprises the steps: obtaining an abnormal event corresponding to an event query instruction and a causal knowledge graph corresponding to a family environment; the causal knowledge graph comprises a plurality of atomic events and causal cohesion scores corresponding to two adjacent atomic events, then searching candidate causal chains corresponding to the abnormal events from the causal knowledge graph, and finally screening out a target causal chain for the event query instruction from the candidate causal chains according to the causal cohesion scores. And the event description information corresponding to the target causal chain is output, so that efficient and accurate complex event tracing is realized, corresponding family events are restored for users, privacy is ensured, meanwhile, real-time and reliable decision support is realized, user query can be responded in real time, reliable event description can be output, and user experience is improved. And the availability of the information and the user experience are greatly improved.

This invention discloses a blockchain-based distributed network intrusion event tracing method and system, belonging to the field of network intrusion tracing technology. The method includes: collecting intrusion event-related data on the distributed node side and establishing a multi-dimensional event fingerprint chain; generating tracing fragments and completing their signatures on the chain; initiating a splicing proposal, with multiple participating nodes voting on the splicing proposal on-chain based on their local verification results and reputation weights; establishing a cross-node attack path sketch; and after global verification of the cross-node attack path sketch through on-chain voting, constructing a tracing pattern library. This invention solves the technical problems of easily tampered distributed network intrusion event tracing data and poor cross-node verification consistency in existing technologies, leading to insufficient accuracy and reliability of tracing results. It achieves secure and accurate tracing of distributed network intrusion event tracing data, improving the accuracy and reliability of distributed network intrusion event tracing.

The application provides a network security event tracing method, device, equipment and medium. In the method, based on the received network security event corresponding event data, an initial investigation graph is constructed, and the initial investigation graph is taken as a current investigation graph; based on the current investigation graph and a decision model, the next investigation action is dynamically determined and executed, the decision model is configured to output the corresponding investigation action according to the investigation state corresponding to the current investigation graph; the investigation feedback data generated after the execution of the investigation action is acquired, and the current investigation graph is updated based on the investigation feedback data; based on the updated investigation graph, the step of determining and executing the next investigation action is iteratively executed until the corresponding tracing result is determined. The scheme is used to solve the problems of poor network attack data tracing analysis effect and insufficient practicability in the related art.

The invention discloses an event tracking method, device and equipment, a medium and a product, relates to the technical field of cloud platforms, and can be applied to the field of financial science and technology. The method comprises the steps of deploying a time sequence database; acquiring event information in the container arrangement system through the event collector; wherein the event information is reported to the container arrangement system by a component in the container arrangement system; the event information is stored in the time sequence database; and obtaining target event information corresponding to a target resource object from the time sequence database through the front-end display system, and integrating the target event information to obtain a life cycle view for event tracking. Through the above technical scheme, full life cycle tracking of the resource object can be realized.

The invention relates to an abnormal event tracing method and device, computer equipment, a readable storage medium and a program product. The method comprises the following steps: acquiring a first total number of historical interaction behavior pairs and a second total number of duration windows with the historical interaction behavior pairs, and acquiring a first probability and a second probability of a first interaction behavior and a second interaction behavior in the duration windows respectively; obtaining mutual information between the first interaction behavior and the second interaction behavior based on the first probability and the second probability, and obtaining a conditional probability of the first interaction behavior relative to the second interaction behavior and a conditional probability of the second interaction behavior relative to the first interaction behavior based on the mutual information; based on the conditional probability, determining that a causal relationship exists between the first interaction behavior and the second interaction behavior; and tracing the abnormal event based on the causal relationship. According to the method provided by the invention, the abnormal event can be accurately traced.

This invention discloses a method, apparatus, and electronic device for tracing and detecting network security incidents, relating to the field of network security protection technology or other related fields. The method includes: monitoring system processes through a trusted terminal; inputting periodically collected system behavior data into an anomaly detection model and outputting anomaly detection results; blocking system processes when abnormal behavior exists in the target system; processing the system behavior data through a semantic proxy to obtain behavior text in natural language form and behavior encoding in vector form; retrieving a preset knowledge base based on the behavior encoding to obtain attack patterns and matching confidence levels matching the system behavior data; and generating a network security incident tracing and handling report based on the behavior text, attack patterns, matching confidence levels, anomaly detection results, and system context information. This invention solves the technical problem in related technologies where data barriers and execution gaps exist in anomaly behavior detection and tracing, leading to delayed response times for network security incidents.