581 results about "Web environment" patented technology

The invention relates to the technical field of earth leakage protection monitoring, and discloses an earth leakage circuit breaker remote monitoring system integrated with the Internet of Things. An electric leakage characteristic modeling module of the system obtains real-time monitoring data, extracts current waveform characteristic parameters, identifies an abnormal waveform mode and a first occurrence time sequence, and generates an original electric leakage characteristic template; the network path generation module performs topological sorting on the monitoring nodes based on the template, establishes an equipment connection path and constructs an Internet of Things topological path; a path anomaly analysis module extracts a node sequence and screens abnormal transmission paths to obtain an abnormal path set; the risk level judgment module collects terminal node risk tags and obtains a risk level tag group through matching; and the topological structure output module counts associated nodes, divides abnormal paths, establishes a mapping relation and generates a remote monitoring topological table. The system improves the accuracy and efficiency of electric leakage monitoring, and is suitable for a complex power network environment.

The invention discloses a TSN scheduling optimization method and device based on flow sensing autonomous learning, equipment and a medium. The method comprises the following steps: deploying a lightweight flow detection module in a switch or a router, and after a controller receives a data request, automatically identifying a newly arrived unknown service flow by using the lightweight flow detection module, and judging whether the newly arrived unknown service flow is a periodic TT flow or an unpredictable burst flow; the controller performs classification management on the identified service flow types, collects topological information and flow requirements of the whole network and issues the topological information and the flow requirements to the terminal nodes through a network management interface; the controller constructs an intelligent queue scheduling task based on the collected network topology information and traffic demand and converts the task into a Markov decision process MDP, network resources, queue states and priorities are used as a state space, a scheduling strategy is used as an action space, a reward function is designed in combination with throughput and delay indexes, and an intelligent queue scheduling task is obtained. Driving a dynamic environment through real-time data and training a DRL model; an enhanced queue scheduling mechanism Pro-CQF is adopted, different priority labels are configured according to classified flow types, and then mixed flow scheduling is carried out; the controller periodically collects time delay, packet loss rate and end-to-end transmission delay indexes and feeds back the indexes to the DRL model, and a scheduling strategy is updated online. According to the method, the traffic sensing and scheduling efficiency is greatly improved in a network environment in which multiple service flows coexist and end-side equipment functions are different, and the reliability and the expandability of the TSN in industrial Internet of Things, edge computing and other high-real-time application scenes are remarkably enhanced.

The invention provides a network security decision-making method and device based on a large language model. The method comprises the following steps: collecting network state data and converting the network state data into natural language description; determining a semantic feature vector corresponding to the natural language description, and retrieving target threat knowledge matched with the semantic feature vector in a knowledge base storing various basic network threat knowledge; generating an analysis prompt text in combination with the target threat knowledge and the natural language description, inputting the analysis prompt text into a large language model, sequentially executing network threat analysis steps indicated in a preset thinking chain according to the analysis prompt text, and determining a network anomaly attribution and a corresponding protection strategy; and issuing the protection strategy to each distributed execution unit deployed in the target network environment, and converting the protection strategy into an equipment configuration command and executing the equipment configuration command. A closed-loop intelligent defense process from information perception to semantic understanding to collaborative response can be realized, and the real-time performance, the accuracy and the expandability of a security decision are improved.

An attack path modeling and discovery system and process of the present combines comprehensive network data with machine learning to determine the greatest risk to a network environment by exposing the path of least resistance an attacker would likely take. This system and process considers both the likelihood of a threat agent to exploit a vulnerability, and the potential for loss when that threat occurs. The system utilizes two key models to accomplish this goal. First, Knowledge Graphs (KG) are leveraged to comprehensively model relationships across an environment, and second, Graph Neural Networks (GNNs) are used to predict the path of least resistance to the network's user-defined most valuable assets.

The invention belongs to the technical field of authority management, and particularly relates to a dynamic authority management system based on an integrated system, which is characterized in that on one hand, dynamic authority portraits of employees are described periodically by integrating multi-system data, and dynamic risk values of real-time operation behaviors of the employees are analyzed based on the latest dynamic authority portraits; on the other hand, through monitoring an organization event queue in real time and analyzing metadata of an event message, an organization event type is identified, a change rule corresponding to the organization event type is matched, an authority synchronization instruction is generated, and transactional operation is started; a behavior risk real-time assessment and event-driven cross-system collaboration mechanism is adopted, automatic and precise dynamic adjustment of the authority is realized, the access control security and management efficiency in an integrated network environment are improved, and in addition, a self-optimization capability based on machine learning is introduced, so that the authority management has the characteristics of continuous learning and evolution.

The invention discloses a traffic scheduling method and an electronic device, and relates to the technical field of traffic scheduling, and the method comprises the steps: determining the priority weight of a micro-service, and predicting a target traffic according to the historical traffic information of a network device; constructing a graph model according to the topological information of the network equipment and the dependency relationship of the micro-service, and performing embedded learning on nodes in the graph model to generate a state vector representing a network state; the priority weight, the state vector and the target traffic of the micro-service serve as input of a reinforcement learning model, and a traffic scheduling strategy of the network equipment is obtained; performing iterative search according to iterative particles formed by encoding the strategy network parameters of the reinforcement learning model and the feature learning network parameters of the graph model to determine reinforcement learning model parameters; and issuing the traffic scheduling strategy to the network equipment and executing the traffic scheduling strategy so as to solve the technical problem that a traffic scheduling method in related technologies is difficult to adapt to a dynamic and complex network environment and service requirements under a micro-service architecture, and the reliability of traffic scheduling is improved.

The invention provides a vision-based cross-network interaction method and system, and relates to the technical field of intelligent interaction, and the method comprises the steps: obtaining a visual interaction sequence, constructing multi-modal feature representation, achieving cross-domain semantic alignment, deconstructing visual information into a hierarchical control instruction set, and transmitting the hierarchical control instruction set to a target network environment for execution after security classification. And a bidirectional mapping relation graph is constructed to realize incremental optimization. According to the method, semantic bridging between heterogeneous networks can be established, the cross-domain control precision is improved, and meanwhile safe interaction in a network isolation environment is guaranteed.

A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user / entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies / threats were previously known. The security platform can include both real-time and batch paths / modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.

An attack detection and source tracing method includes acquiring entities in a target network environment and interaction event information between the entities and constructing a network event graph with the entities and the interaction event information; determining a graph embedding vector of each interaction event information in the network event graph as feature information based on a preset attack feature recognition model and determining an attack event in the network event graph according to the feature information; determining dependencies between the attack event and remaining interaction event information in the network event graph and searching for a corresponding interaction event information as source tracing information of the attack event according to the dependencies.

The invention discloses a malicious DoH tunnel traffic detection method and device and a storage medium, and relates to the technical field of network security, and the method comprises the steps: obtaining a to-be-detected traffic, and extracting a plurality of to-be-detected traffic features of the to-be-detected traffic; inputting each to-be-detected traffic feature into a target malicious traffic detection model for detection, and obtaining a malicious traffic detection result output by the target malicious traffic detection model, the target malicious traffic detection model is obtained by training a malicious traffic feature data set after important feature screening, semantic enhancement and semantic processing. According to the method, redundant and irrelevant features are removed through important feature screening, key information is focused, malicious traffic semantics are highlighted through semantic enhancement, and environmental noise interference is inhibited; and the flow features are deeply modeled through semantic processing, so that the model detection accuracy is high, the model can adapt to complex and changeable network environments and flow modes, and the robustness and generalization ability of the model are improved.

The invention discloses an LSTM electric power Internet of Things ring main unit optimization method, system, device and medium, and belongs to the technical field of electric power Internet of Things management and data analysis, and the method comprises the steps: collecting communication state and network environment data in real time, and generating a multi-dimensional feature matrix through dynamic standard score standardization and derivative feature calculation; dynamically adjusting an LSTM forgetting gate weight based on the bandwidth fluctuation index, and outputting an equipment performance score; constructing a dynamic scoring algorithm and triggering a differentiated maintenance instruction in linkage with a multi-threshold scene strategy; a closed-loop feedback mechanism is adopted to screen high-deviation data, new scene training is enhanced through a dynamic loss function, and minute-level hot updating of the model is achieved; the method solves the problems of static threshold misjudgment, poor environment adaptability of the prediction model and single decision-making mechanism, remarkably improves the feature quality, the equipment evaluation precision and the resource allocation rationality, and strengthens the intelligent operation and maintenance capability of the system.

The invention discloses a graph structure-based domain penetration attack path generation method, which belongs to the technical field of network security, and comprises the following steps of: constructing a multi-level relation graph comprising a host node, a service node and a user node through automatic detection by taking any host in a domain as a starting point; assigning a weight attribute to the atlas edge based on a vulnerability library and an attack pattern library; an improved heuristic graph search algorithm is adopted, all feasible attack paths and threat scores thereof are generated by integrating the path length, attack difficulty and permission improvement effect, and the problem that the threat scores of all the feasible attack paths are influenced in various scenes and dynamic change domain environments is solved. The technical problems of realizing comprehensive automatic penetration testing, accurately identifying potential attack paths and establishing a systematic threat assessment mechanism are solved, the automation, intelligence and high-efficiency level of domain penetration testing is remarkably improved, and the method has good adaptability, expansibility and practical value and is suitable for popularization and application. And attack path discovery and risk early warning work in a dynamic network environment with high security requirements can be effectively supported.

The invention discloses a multi-dimensional data asynchronous calculation method and system based on a dynamic dependency graph, and relates to the field of data processing. The method comprises the following steps: constructing a metadata, logic and instance three-layer separation storage model; analyzing the reference relationship to construct a directed acyclic graph, and generating a calculation priority; monitoring data change, and executing asynchronous serialization calculation through a message queue based on priority; the associated document is automatically updated based on anchor mapping. According to the method, the calculation deadlock and the performance bottleneck of large-scale data in the Web environment are solved, logic decoupling and dynamic expansion are realized, the final consistency of the data is guaranteed, and the high-concurrency throughput and the stability are remarkably improved.

The invention belongs to the technical field of advertisement putting management, and particularly relates to an intelligent precise advertisement putting optimization method and system based on dynamic strategy adjustment. The system comprises a user behavior deep insight module, a market dynamic perception module, an advertisement effect intelligent evaluation module, a strategy dynamic generation module, an advertisement intelligent putting execution module and an advertisement putting management end. Various behavior data of users in a network environment are collected and analyzed through the user behavior deep insight module, the market dynamic sensing module monitors and analyzes changes of the market environment in real time, and the advertisement effect intelligent evaluation module evaluates the actual effect of advertisement putting. And the strategy dynamic generation module dynamically generates and adjusts the advertisement putting strategy, the advertisement is accurately put to the target user according to the advertisement putting strategy, the advertisement putting is comprehensively upgraded from multiple dimensions of accuracy, timeliness, effect optimization and user experience, and the increasingly complex and variable advertisement putting requirements are met.

According to the large file uploading method and device, the electronic equipment and the storage medium provided by the invention, the operation environment parameters of the target client are collected, and the file uploading strategy containing the data block size, the concurrent transmission quantity and the retry mechanism is dynamically generated based on the parameters; meanwhile, according to the strategy, the file to be uploaded is divided into a plurality of data blocks and integrity verification is executed, the uploading state of each data block is persistently stored in the uploading process, and uploading of the uncompleted data blocks is recovered based on the uploading state after transmission interruption is detected. The problems that due to the fact that a fixed fragment size and a static concurrent strategy cannot adapt to different device performance and network environments, the uploading state is lost after page refreshing or browser restarting is caused by depending on browser cache, the verification efficiency is low, and uploading fails, resource utilization is not good, and uploading starting is delayed can be solved. The technical effects of improving the environmental adaptability, the resource utilization efficiency and the uploading success rate of Web cloud disk large file uploading are achieved.

The present disclosure provides a system and methods for cyber risk management. The system determines risk values for a network environment having one or more assets based on asset weights of the assets and impact vectors of one or more vulnerabilities associated with the assets. The system iteratively generates one or more attack paths using the vulnerabilities, and applies one or more security controls to mitigate the vulnerabilities to prevent attackers from attacking the network environment using any of the attack paths.

The invention relates to the technical field of cloud computing and intelligent office, in particular to an intelligent printing task allocation and scheduling optimization method based on cloud collaboration, which comprises the following steps of: constructing a multi-dimensional task feature set fusing task attributes, equipment states and network environments; generating an optimal task-equipment mapping relation by introducing a matching degree function and an improved genetic algorithm; when the equipment load fluctuates, a scheduling instruction is dynamically generated based on the equipment topological graph; performing attribute encryption and homomorphic encryption processing on the scheduling instruction to form a secure transmission unit; and through a cloud and edge collaborative verification mechanism, task execution security and consistency are ensured. The method has the advantages of high-adaptability scheduling, load-aware dynamic correction, privacy enhancement execution control and the like, and the text and print resource utilization efficiency and the system intelligence level are improved.

The invention discloses an application preloading method and device, equipment and a storage medium, and relates to the technical field of application management, and the method comprises the steps: obtaining user behavior data of a target user and current network environment data; inputting the user behavior data into a user preference prediction model for preference analysis to obtain user preference information output by the user preference prediction model; inputting the user preference information and the current network environment data into an application recommendation engine for recommendation analysis to obtain an application recommendation list and a resource preloading strategy output by the application recommendation engine; and based on the resource preloading strategy, performing application preloading on the application recommendation list through a preset back-end cache library. According to the application, the application needing to be preloaded is selected through the user preference and the network environment, unnecessary resource loading is avoided, the resource utilization efficiency is improved while the loading time is remarkably shortened, personalized application recommendation is provided for the user, and the personalized requirement of the user is met.

The invention relates to a deterministic service-oriented resource scheduling method, apparatus and device, a medium and a program product. The method comprises the following steps: modeling a deterministic service into a directed acyclic graph; therefore, the processing flow of the deterministic service can be represented by the directed acyclic graph, so that the intelligent agent can identify the execution overhead of each task on the computing node according to the directed acyclic graph, and a basis is provided for subsequent scheduling decisions. Determining a real-time state of each computing node in the heterogeneous computing environment; therefore, the current data processing capacity of each computing node in the complex heterogeneous computing environment can be mastered in real time, and the task load of each computing node can be balanced conveniently. And based on the directed acyclic graph corresponding to the deterministic service and the real-time state of each computing node, outputting a scheduling decision of the deterministic service through the trained agent. Therefore, computing and communication resources can be dispatched cooperatively under a unified converged network architecture, so that the computing and communication resources can adapt to a complex and changeable network environment, and an optimal dispatching decision is output.

The invention provides a building construction carbon emission real-time monitoring and intelligent analysis system based on the Internet of Things, relates to the technical field of carbon emission monitoring and analysis, and solves the problems of functional deficiency and imperfection of a carbon emission monitoring system. In the system, a sensing layer is used for collecting multi-dimensional carbon emission related original data of a construction site in real time and carrying out edge side preprocessing; the transmission layer is used for transmitting data by adopting a self-adaptive multi-mode communication protocol and adapting to the network environment change of a construction site; the platform layer is used for receiving and integrating data, executing carbon emission accounting, performing multi-dimensional intelligent analysis, constructing and updating a digital twinborn simulation model and driving an intelligent analysis process; and the application layer is used for visually and dynamically presenting system information data, providing interactive access and early warning, and opening key carbon emission data and supervision support to a government supervision platform. The method is optimized and improved from multiple aspects, so that the system has relatively high application efficiency and meets the requirements of domestic and overseas carbon auditing.

The invention discloses an Internet of Things intelligent risk processing method and related equipment thereof, belongs to the technical field of artificial intelligence, and is applied to intelligent risk control and transaction risk management of a financial system. According to the method, the device state, the time sequence data and the spatial topological relation are combined by obtaining the multi-dimensional parameters such as the device operation state, the network environment and the service scene and constructing the context feature vector. In a risk early warning analysis link, the layered intelligent agent accurately predicts local and global risks through a space-time association mechanism, and feeds back a prediction result to a state space to drive dynamic adjustment of control parameters. And in combination with the online optimization capability of the reinforcement learning algorithm, the control strategy can automatically adapt to the real-time change of the equipment state, and the collaborative effect of quick response of the equipment end, local optimization of the edge end and global regulation and control of the cloud end is realized. According to the invention, the timeliness and accuracy of risk early warning are improved, and the adaptive and intelligent management capability of the system in a complex network environment is enhanced.

Disclosed embodiments relate to systems and methods for centrally analyzing and managing source code. Techniques include identifying, at a centralized resource in a network environment, a first source code; identifying the first source code as a candidate for an execution of an access control action; identifying, at the centralized resource, a security risk indication for the first source code, the security risk indication being based on permissions associated with a functionality of the first source code; performing, based on the security risk indication, at least one of: developing a least privilege set of permissions for the source code, or modifying the least privilege set of permissions.

The invention discloses a Web-based visual editing method, belongs to the technical field of industrial configuration, and aims to solve the problems of complex deployment of traditional configuration software and insufficient Web scheme performance. The method comprises the following steps: constructing a front-end architecture (Vue. Js + Konva.js) containing a graphic element module, a canvas management module and the like; the primitive adopts JavaScript prototype chain inheritance + SVG / Canvas double-layer rendering, and a canvas is divided into four layers and is provided with a quadtree index; an editor and an expression engine are generated by using a factory pattern for attribute configuration; page management supports state capture recovery; real-time communication is based on WebSocket + PubSub, and data aggregation and incremental updating optimization are combined. Cross-platform zero deployment and Web environment near-desktop performance are achieved, editing efficiency is improved, industrial protocols such as OPC UA are compatible, and the method is suitable for the field of energy and intelligent manufacturing.

A system and method for privilege assurance protection of computer networks that remedies the deficiencies of the current directory service structure. The system uses a software agent to collect and store snapshots of all network resources on a computer network by identifying network domains, searching the directory service of each domain for network resources, and periodically querying the network resources for changes. The software agent communicates with a backend server which provides searching, querying, storage, administrative and other functionality to the agent via remote procedure calls.

The invention provides a service debugging method and device, electronic equipment and a computer readable storage medium, and relates to the technical field of service debugging. Initiating a debugging request for a target service instance based on a local agent, and obtaining a short-term security credential by the local agent; wherein the short-term security credential comprises the target service instance identifier; establishing, by the local agent, an encrypted communication channel with a remote agent using the short-term security credential; the remote agent extracts the target service instance identifier from the short-term security credential and obtains a real-time network address of the target service instance; and sending, by the remote agent, the received debugging traffic to the real-time network address of the target service instance. Identity authentication and authorization are realized through a short-term security certificate, and security and credibility of a debugging request are ensured; the security risk in the debugging process is reduced, and the flexibility and efficiency of cross-network environment debugging are enhanced.

The invention belongs to the technical field of bidding business informatization, and provides an Office plug-in-oriented offline-online mixed bidding document intelligent editing and auditing system, which comprises a localized plug-in module, a bidding document editing module, a bidding document editing module, a bidding document editing module, a bidding document editing module, a bidding document editing module and a bidding document editing module, the content generation module converts the bid invitation terms into knowledge base query statements and generates a dynamic filling template; the double-model verification module carries out format and semantic double review through cooperation of a local lightweight model and a cloud large model; the offline data security module supports writing of a bidding document in an offline state, temporarily stores sensitive data in the bidding document into a local encryption sandbox, and performs data synchronization after network recovery; the version comparison module tracks a DOM node change path between bidding document versions and generates a difference report of bidding documents of different versions; through deep integration of offline operation and online collaboration and based on localized operation support of the Office plug-in, a user can edit the bidding document in real time in a network-free environment, and the method adapts to the flexibility requirement of a bidding scene.

Techniques for protection scheme configuration in a communication network are disclosed. For example, a home communication network of given user equipment sends protection scheme configuration data to the given user equipment using a user equipment parameter update procedure, or a steering of roaming procedure in a visited communication network scenario.

A system and method for the dynamic authentication revocation using privilege assurance of enterprise computer network environments using lateral movement detection and prevention. The system uses local session monitors to monitor logon sessions within a network, generating and verifying event logs and authentication records to ensure the legitimacy of authenticated user sessions and to revoke credentials when an illicit session is detected and further removing potentially compromised network components from the network, halting lateral movement in real-time.

The invention provides a method and a device for testing compatibility of a server operating system, which can improve the speed and the quality of compatibility testing. The server operating system compatibility test method comprises the following steps: acquiring a task script and test parameter configuration; wherein the task script comprises a process of testing the compatibility of the operating system, and the process of testing the compatibility of the operating system comprises at least one of downloading a test script, configuring an offline source, installing a test tool, initially preparing an environment and executing an actual test; generating an assembly line task based on the task script; starting an assembly line task based on a test instruction and the test parameter configuration; wherein the assembly line task runs on a server for deploying an assembly line, and the server for deploying the assembly line and the server to be tested are in the same network environment; and based on the started assembly line task, performing assembly line testing on the to-be-tested server.

The invention discloses a cross-virtual private cloud network scheduling method based on a cloud computing infrastructure, a cross-virtual private cloud network scheduling system based on the cloud computing infrastructure, electronic equipment and a readable storage medium, and the method comprises the steps: obtaining network configuration information of a virtual private cloud; establishing a cross-virtual private cloud access channel according to the network configuration information, wherein the access channel comprises a peer-to-peer connection channel and a terminal node channel; configuring an address translation rule and a routing rule for the access channel; and carrying out forwarding and access control on the network access flow among the applications and / or the computing resources in the virtual private cloud according to an address conversion rule and a routing rule. Uniform configuration and dynamic management of the network access path are realized while independence of each virtual private cloud is kept, so that the access relationship across the virtual private cloud is clearer, configuration is more concentrated, operation and maintenance are more simplified, and interconnection flexibility and manageability in a cloud multi-network environment are improved.