314 results about "Network domain" patented technology

The invention discloses an optical transmission cross-domain service real-time configuration method, an optical transmission cross-domain service real-time configuration device and a computer program product, and aims to realize unified planning and dynamic output of cross-domain service end-to-end service quality targets by constructing a multi-domain quality strategy fusion model and integrating service quality strategies and resource states of different network domains. By collecting performance data of each domain in real time and combining with a time sequence analysis algorithm, the network performance degradation trend can be accurately identified; based on quality propagation path analysis of a cross-domain service topological relation graph, a quality degradation root can be quickly positioned, the influence range of the quality degradation root can be quantified, and the service quality stability of a key service in a resource limited scene is ensured; by establishing a cross-domain service quality mapping system, heterogeneous network performance parameters are mapped to end-to-end service quality indexes, and the cross-domain collaborative operation and maintenance efficiency is greatly improved. A continuous iterative optimization mechanism driven by reinforcement learning is adopted, adaptive adjustment of network resource allocation and a routing strategy is realized, and a cross-domain service quality dynamic optimization closed loop is formed.

The invention relates to the technical field of network communication, and discloses an intelligent control method and system of a switch. The method comprises the following steps: receiving a heterogeneous data stream in a target network domain; performing data processing by using a preset flow feature aggregation model, and generating a flow dynamic pressure field distribution diagram and a protocol priority mapping matrix; constructing an adaptive scheduling threshold model, and generating a multi-target flow control instruction set; a cascade effect is simulated based on a network congestion chained conduction model, and collaborative routing parameters are optimized; and iteratively optimizing through a mixed integer programming framework, and outputting a network scheduling action sequence to a switch control engine. The system correspondingly comprises a data receiving module, a data processing module, an instruction generation module, a simulation optimization module and an instruction output module. According to the method, heterogeneous data can be effectively processed, congestion can be accurately predicted, flow control can be optimized, the overall performance of the network can be improved, and communication requirements in a complex network environment can be met.

The invention relates to the technical field of data processing, can be applied to business scenes of financial science and technology, medical health, lease and the like, and discloses a distributed multi-terminal data cooperative processing method, which comprises the following steps: receiving a structured data unit containing business logic generated by an initiating terminal, and transmitting the structured data unit to a business verification server, receiving verification result data returned by the service verification server, and performing security encapsulation processing on the verification result data to generate security encapsulation data; calling a distributed communication service interface of the distributed operating system, and detecting a connectable device set in a network domain where the initiating terminal is located; and establishing a multi-path transmission link based on the transmission capability parameters of the terminal devices in the connectable device set, and distributing the security encapsulation data to the target terminal device group through the multi-path transmission link. According to the invention, efficient distribution and synchronization of data are realized through a multipath transmission link, the dependence on a background system is reduced, the timeliness and consistency of data synchronization are improved, and the maintenance cost of the system is reduced.

Techniques disclosed in the present disclosure relate to communication networks and methods for supporting time-sensitive deterministic communication based on a time-sensitive network (TSN) mechanism. A communication network may include a plurality of network domains in the communication network connecting each other, and a plurality of schedulers in the plurality of network domains. A respective of the plurality of schedulers may compute a local schedule for a respective of the plurality of network domains, and a first scheduler and a second scheduler of the plurality of schedulers may iteratively exchange a first local schedule and a second local schedule. The first local schedule and the second local schedule may include different cycle times. The first network domain may transmit interdomain ethernet link information related to a link connecting the first network domain and the second network domain, and intradomain schedule information related to the first local schedule.

The invention provides an SDN (Software Defined Network) inter-domain traffic engineering method based on reinforcement learning, which comprises the following steps of: deploying a data traffic demand monitoring platform and a control system, and constructing a global network topological graph; calculating a short link identifier for the link in the network and distributing the short link identifier to each network device; flow judgment is carried out, upward notification is carried out according to requirements, and pre-operation of intelligent routing is cooperatively completed; deploying a reinforcement learning model in the total intelligent body, outputting an optimal cross-domain path strategy to the cooperative controller, disassembling the optimal cross-domain path strategy into flow table rules which can be executed by each domain, and issuing the flow table rules to local controllers of related domains; and each local controller pushes the flow table configuration to the domain switching equipment to complete the forwarding decision of the flow. According to the method, a complete closed-loop process of flow measurement, intelligent decision making, cross-domain control and path issuing is realized, feasible reference is provided for actual deployment of an intelligent network, and the method has good engineering popularization value and is suitable for intelligent scheduling scenes such as an operator backbone network, an industrial internet and metro edge cloud.

The invention provides an adaptive path selection system based on GNN and multi-agent DRL, which is based on a layered multi-domain SDN architecture and comprises a root server layer, a domain controller layer and a data layer. The root server layer comprises a root server and a root agent, and the root agent is used for calculating a global routing path strategy and optimizing and adjusting a routing path according to feedback of a local network domain. And the root server distributes the routing path to a domain controller layer according to a routing path strategy to carry out routing path forwarding and adjustment of a local network domain. The domain controller layer comprises a plurality of domain controllers and domain intelligent agents, the domain controllers construct a topological structure composed of boundary switches, and a routing decision is made in a local domain according to an optimal global routing path strategy. And the domain intelligent agent performs modeling analysis on the topological structure by using a deep reinforcement learning algorithm in combination with a graph neural network to realize intra-domain path selection. And the data plane layer feeds back the network topology information to the domain controller, and receives and executes a routing decision sent by the domain controller at the same time.

The invention discloses a causal chain tracking method and system for cross-space APT attack behaviors, and relates to the technical field of network security. The method comprises the following steps: collecting heterogeneous device logs crossing multiple network domains, extracting original attack data, performing spatial-temporal feature extraction, and generating a device behavior spatial-temporal vector; analyzing the original attack data to obtain attack tactical semantic features, fusing the equipment behavior space-time vector and the attack tactical semantic features, and constructing a three-dimensional association map; and performing attack path reasoning on the three-dimensional association map based on a causal discovery algorithm, identifying a causal dependency relationship, performing data tracking according to the causal dependency relationship, reconstructing an APT attack causal chain, and obtaining an attack logic path. The technical problem that in the prior art, comprehensive and accurate traceability analysis on cross-space APT attacks is difficult is solved, and the technical effects of efficient reconstruction of APT attack causal chains and accurate identification of attack paths are achieved.

Methods and apparatus for biometric data maintenance, access and distribution across two or more experiential and / or network domains. In one embodiment, a 5G NR-based network architecture is provided which allows ultra-low latency and effectively user-imperceptible biometric data use for e.g., authentication and maintenance of user state across multiple domains via multiple constituent user devices (e.g., UEs). The network architecture includes both (i) a distributed biometric database (BDB) model wherein relevant biometric data for individuals / UEs is intelligently cached in various portions of the distributed database, and (ii) centralized and local BAEs (biometric analytics entities) which manage the aforementioned intelligent caching, as well as network configuration using one or both of 5G NR network “slicing” and CU / DU split options to optimize end-user biometric-related applications such as those providing identification / authentication, AR functions, VR functions or yet others.

The invention discloses a secure sharing exchange method and system based on double unidirectional optical shutters. The method comprises the following steps: respectively deploying a sharing exchange service in two networks isolated by optical gates, and registering interface information of business applications needing cross-optical-gate interaction on the sharing exchange services; each network comprises a database which is used for storing registration information, a transmission record, a transmitted application name, a transmission state, transmission time, transmission content and a return result; through an application registration step and a unique interface name of the whole domain, on the basis of not leaking an IP and a port to different security network domains, service application cross-optical-shutter file transmission and HTTP parameter request are realized based on a TCP / IP protocol, and the invasiveness to a service application code is reduced; according to the invention, monitoring of data transmission is realized in a transmission process; and after the transmission is completed, the receiving side returns the transmitted application name, the transmission parameter or the file name and the sending time to the transmission initiating side to form a transmission closed loop.

The invention relates to a cross-network domain security data interaction method and device based on dynamic multi-channel and intelligent verification, computer equipment, a computer readable storage medium and a computer program product, and is applied to an external network domain. The method comprises the following steps: acquiring network state data of each available transmission channel between an internal network and an external network, and determining a transmission priority score of each available transmission channel so as to screen out a main transmission channel and a standby transmission channel; dynamically distributing to-be-transmitted data fragments to the main transmission channel and the standby transmission channel through a reinforcement learning algorithm; transmitting the data fragments distributed to the main transmission channel and the standby transmission channel to an isolation domain; the isolation domain is used for filtering the received data fragments through a hardware filtering engine and sending the filtered data fragments to the internal network domain; the internal network domain is used for verifying the integrity of the data fragments according to the fragment hash values corresponding to the data fragments. By adopting the method, the intelligence of data transmission in the internal and external network interaction process can be improved.

The invention discloses a large-scale low-orbit satellite network domain-division intelligent routing method, which belongs to the technical field of satellite communication, and comprises the following steps: constructing a network model based on multi-dimensional resource characteristics, and providing resource constraint conditions and space-time correlation characteristics for routing decision by combining with a regional flow prediction algorithm of an improved Transform architecture; virtual nodes and an autonomous domain are divided based on a geographic area, and a low-orbit satellite network routing process is decoupled into an intra-domain part and an inter-domain part; a multi-agent deep Q network is adopted in a domain, a sum tree mechanism-based deep Q network is adopted between domains, a routing algorithm and a resource scheduling algorithm are respectively designed, and a domain intelligent routing system with flexibility and expandability is constructed through hierarchical routing and resource decoupling scheduling. According to the method, the service capability of the low earth orbit satellite network in extreme scenes such as topology high-frequency change, strict resource limitation and traffic space-time mutation is remarkably enhanced, and a high-reliability and low-delay routing solution is provided for space-ground integrated communication, emergency disaster early warning and global real-time data transmission.

A communication method and a related device are applied to the field of network awareness. In the application, a first node can obtain accumulated time delay information of N routing paths, and determine a target routing topology between the first node and a root node at least based on the accumulated time delay information of the N routing paths, the first node and the root node belong to the same network domain, and the path through which the message of the first node passes when being transmitted in the network comprises the first node and the root node. The shorter the time delay of message transmission between the nodes in the network domain is, the higher the stability of message transmission of the routing topology passing through the shorter time delay is, so that the target routing topology of the node transmission message in the same network domain is screened out from the obtained accumulated time delay information of the N routing paths, and the stability of the message transmission of the node transmission message in the network domain is improved. A low-delay message transmission routing path can be coordinated among the nodes. And the message of the node is transmitted through the target routing topology, so that the reliability of the end-to-end delay can be ensured.

The invention discloses a network security multi-target monitoring system and monitoring method based on monitoring data, and aims to solve the problems that the existing network security monitoring technology is insufficient in single-point monitoring, lacks multi-target comprehensive evaluation, is difficult to adapt to a dynamic network environment, lacks an effective early warning mechanism and the like. The invention provides a network security multi-target monitoring method and system based on monitoring data. The method comprises the following steps: dividing a target monitoring network into a plurality of sub-network domains, arranging a network traffic feature acquisition module in each sub-network domain, acquiring first and second traffic data, and extracting abnormal features in combination with an attack frequency; cloud data is used to calculate the security margin and the security margin index of each sub-network domain, and then the security uniformity and the security change trend of the target monitoring network are evaluated; and performing early warning according to the historical data and the current trend.

Procedures, methods, architectures, apparatuses, systems, devices, and computer program products for enabling computing aware traffic steering (CATS) using internet protocol (IP) address anchoring are described. One method may include receiving a request for a service that is offered by two or more nodes in a network domain associated with a network element. The request comprises information indicating an identifier associated with the service and CATS requirements to assist the network element to determine which one of the nodes to select to instantiate the service. The method may include determining, based on an ability of the nodes to provide the service under the CATS requirements, which one of the nodes to select to instantiate the service, and sending information indicating an allocated internet protocol (IP) prefix associated with the selected one of the nodes that is instantiating the service.

There are provided measures for performance related management of artificial intelligence or machine learning pipelines in cross-domain scenarios. Such measures exemplarily comprise transmitting a first artificial intelligence or machine learning performance related message towards a second network entity managing lifecycles of artificial intelligence or machine learning pipelines in a first network domain in a network, and receiving a second artificial intelligence or machine learning performance related message from said second network entity, wherein said first artificial intelligence or machine learning performance related message comprises a first information element including at least one first cross-domain network service involved artificial intelligence or machine learning pipeline performance related parameter.

The invention discloses a network attack tracing method, device and equipment and a medium, and the method comprises the steps: obtaining a plurality of network flow data packets, a plurality of pieces of weblog data and a plurality of equipment state parameters of a plurality of monitoring nodes in a target network domain; determining an abnormal node with a network attack behavior in the plurality of monitoring nodes based on the plurality of network flow data packets, the plurality of pieces of network log data and the plurality of equipment state parameters; and tracing the network attack behavior based on the abnormal data packet of the abnormal node, the abnormal weblog data and the abnormal equipment state parameter to obtain an attack type, an initial attack node and an attack path of the network attack behavior. The collaborative analysis value of data packet deep features and multi-source equipment information is fully utilized, real threats and normal network activities are accurately distinguished, and the traceability accuracy and reliability are remarkably improved. Meanwhile, through correlation analysis of multi-dimensional data, an attack source positioning range can be converged step by step, and an attack path can be completely reconstructed.

The invention relates to the technical field of information security, in particular to a cluster self-discovery method suitable for a cloud server cipher machine, which comprises the following steps: when physical equipment of the cloud server cipher machine leaves a factory, a certificate management module generates an equipment certificate and a root CA certificate in combination with an enterprise CA system, and stores the equipment certificate and the root CA certificate; after the virtual cipher machine is created and started, the key management service module combines with the certificate management module to generate a virtual machine certificate, and stores the virtual machine certificate, the storage device certificate and the root CA certificate together; the cluster management service module enables the master node of the virtual cipher machine to discover the slave node of the virtual cipher machine in the same network domain through UDP broadcast, and executes three-level verification on the slave node of the virtual cipher machine from three aspects of an equipment certificate, a virtual machine certificate and an authentication signature; and the virtual cipher machine master node synchronizes the cluster master key to the virtual cipher machine slave node passing verification. According to the invention, hierarchical identity isolation and verification of the cloud server cipher machine host and the virtual cipher machine can be realized, and the security of cluster self-discovery and authentication stages is ensured.

The invention belongs to the technical field of network communication, and discloses a service network message cross-domain transmission method and system based on SRv6SID function extension. According to the method, a service network identifier is embedded in an Args field of the SRv6SID, the service network identifier comprises a service network type (TYPE) and a service virtual group tag (VGT), and service awareness transmission of a cross-domain network is realized in combination with an intelligent routing decision driven by deep reinforcement learning. Compared with the prior art, the protocol compatibility can be ensured, the transmission delay and the protocol overhead can be remarkably reduced, the transmission flexibility, the high efficiency and the customizability of the service network message among different network domains can be improved, and the method and the device are suitable for scenes such as 5G, industrial internet and the like.

The invention discloses a self-adaptive distributed network integration system and method for virtual and real unmanned aerial vehicle cooperation, and relates to the technical field of unmanned aerial vehicle control, the system comprises a central control plane and at least one node agent, the central control plane comprises a global identity manager configured and distributed with globally unique network identity information, recording and recovering the network identity information; the network topology and state manager is configured to generate a virtual and real network state view, responds to query and issues a network simulation instruction to the node agent; the distributed network coordinator is configured to decide and coordinate the node agents to construct a cross-host logic two-layer network domain; the security policy manager is configured to define and store a network access control policy of the virtual unmanned aerial vehicle; the adaptive distributed network integration system and method aim to realize physical presentation of the virtual unmanned aerial vehicle on the network level, so that the virtual unmanned aerial vehicle can directly communicate with and collaboratively work with a real unmanned aerial vehicle in the same network plane.

The invention relates to the technical field of wireless communication, and provides an ultra-low time delay cooperative communication method and system, and the method comprises the steps: constructing an end-to-end network slice strategy model which comprises a wireless access network, a bearer network and a core network based on a service level protocol; fusing vehicle-mounted and roadside heterogeneous sensing data, constructing surrounding environment situation sensing data, and generating an uplink data packet with a service type identifier; a dynamic decision is made according to a service type identifier in the uplink data packet, a collaborative scheduling logic mechanism is triggered, end-to-end transmission is completed in each network domain, and a multi-access edge computing data packet is output; and performing real-time analysis on the multi-access edge computing data packet, generating a final control instruction or early warning information, and completing closed-loop issuing through a downlink. According to the invention, end-to-end network resource hard isolation and cloud end-to-end integrated cooperative intelligence are cooperatively fused, and a whole-process deterministic service system from multi-source sensing, guarantee communication and cooperative decision-making to closed-loop control is constructed.

The invention discloses a decentralized AI service credible management system and a decentralized AI service credible management method. According to the method, the client and the server of each network domain are constructed through the credible AI model based on federal learning, so that the credibility of the AI model obtained by training can be ensured; the block chain node in each network domain can evaluate the credibility of the AI model uploaded to the block chain by the server of each network domain through the AI model credibility evaluation based on logistic regression and clustering, thereby supporting the subsequent personalized AI service. Through on-chain registration, under-chain storage and authorization access control of the AI model realized based on the client, the server and the block chain network, block chain-based AI service management is realized, and decentralized management of the whole life cycle of the AI service can be realized.

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 relates to a link planning method based on cross-domain heterogeneous network intelligent fusion, and the method comprises the steps: collecting heterogeneous data from a network, and carrying out the preprocessing of the data; fusing the features of different network domains; evaluating the importance of each link in the heterogeneous network according to the low-dimensional feature matrix; initializing a link population, calculating population fitness, and constructing a population dynamic model; calculating a link resource allocation proportion, updating a link topology according to the link resource allocation proportion, increasing the bandwidth of a high-proportion link or reducing the load of a low-proportion link, and generating an optimized topology; and obtaining a link planning decision by using reinforcement learning according to the optimized topology, and evaluating the link planning decision and performing adaptive adjustment through a feedback mechanism. According to the invention, the data transmission efficiency is improved, and seamless integration and extended application of a multi-domain network are supported.

The invention relates to a deterministic resource management method in a hierarchical computing power network architecture, and belongs to the technical field of computer networks. According to the invention, a hierarchical and domain-divided deterministic computing power network architecture based on threshold alarm and a deterministic resource management method thereof are constructed; the whole network is provided with a first-level network controller and is divided into different second-level network domains, each second-level domain is provided with a second-level network controller, and each second-level domain provides deterministic service; reinforcement learning agents are arranged in the first-level network controller and the second-level network controller, and the first-level agent obtains routing resource utilization rates, alarm states and current service information under all service flow categories in current second-level domains and decides to refuse to accept the service or select an optimal deterministic routing path for the service; and the secondary intelligent agent adjusts the service resource configuration proportion of the secondary intelligent agent and feeds back whether the service is successfully accepted or not. According to the invention, the utilization rate of network resources and the service acceptance rate are improved, and the occupation of computing resources and transmission resources during service acceptance is reduced.

The invention discloses a multi-channel integrated radio frequency system based on double-threshold interference detection and dynamic spectrum aggregation. A radio frequency front-end unit is used for realizing broadband spectrum access and performing analog-to-digital conversion; the digital channel processing unit is used for realizing channelized segmentation through up-conversion and down-conversion, carrying out band elimination filtering to shield unavailable channels and outputting filtering parameters to support dynamic channel recombination; the digital signal parallel processing unit performs parallel access by using the divided channels; the spectrum sensing unit is used for carrying out double-threshold channel interference detection and real-time spectrum analysis according to the parallel access signals; and the frequency spectrum decision-making unit is used for judging the channel state and fusion detection judgment according to the interference detection result, judging the availability of a specific channel in the data link network and carrying out cooperative dynamic frequency spectrum aggregation. According to the method, a consistent spectrum access decision is realized by adopting a spectrum monitoring, sensing convergence and fusion decision mechanism, and consistent understanding of an available frequency set and high-reliability network domain dynamic spectrum aggregation are guaranteed.

The invention discloses a 6G-oriented cross-domain knowledge-driven network intelligent scheduling system and a 6G-oriented cross-domain knowledge-driven network intelligent scheduling method. The architecture comprises a cross-domain knowledge collaborative evolution module, a network closed-loop management module and a multi-normal-form learning decision module, the cross-domain knowledge collaborative evolution module is used for disassembling a network state into an environment domain, a network domain and a user behavior domain, and online incremental fusion of three-domain knowledge is realized through a graph neural network; dynamically updating the global knowledge base based on knowledge distillation; the network closed-loop management module is used for constructing a function closed loop of perception-reasoning-knowledge generation-decision issuing-verification optimization-memory retrieval; and the multi-normal-form learning decision module is used for fusing meta learning, reinforcement learning, federal learning and self-supervised learning to realize rapid migration and continuous evolution of the strategy. According to the method, the network data throughput, the fault recovery speed, the flow prediction precision, the resource fairness, the path efficiency and the task success rate are improved, and the method is suitable for complex 6G scenes such as air-ground integration and low-altitude traffic control.

The invention discloses a cross-network domain HTTP proxy method and device based on a message queue and a storage medium, and the method comprises the steps: serializing an HTTP request of a client into a request message in a ProtoBuf format through a local proxy server, and transmitting the request message to a message queue system, so that the message queue system forwards the request message to a remote proxy server; the remote proxy server deserializes a request message into an HTTP request and sends the HTTP request to the server, and then serializes an HTTP response returned by the server into a response message in a ProtoBuf format and sends the response message to the message queue system, so that the message queue system forwards the response message to the local proxy server; and deserializing the response message into an HTTP response through the local proxy service and returning the HTTP response to the client. The method improves the efficiency and reliability of cross-network domain communication, and can be widely applied to the technical field of computer networks.

The invention relates to the technical field of network space security, and provides a cross-domain honey array collaborative deployment method, device and equipment based on federated learning, and the method comprises the steps: dividing a plurality of network domains into a plurality of autonomous domains, and deploying a local honey array agent module in each autonomous domain; collecting local honey point interaction information in the autonomous domain according to each local honey array agent module; training a local honey spot decoy effectiveness evaluation model according to the local honey spot interaction information, and outputting local model parameters corresponding to each autonomous domain; according to the local model parameters corresponding to each autonomous domain, generating a global honey point deployment strategy through weighted aggregation of a federated learning aggregator; based on the global honey point deployment strategy, a local honey point deployment strategy of each autonomous domain is generated through a cross-domain scheduling mechanism module; according to the local honey point deployment strategy of each autonomous domain, deployment configuration of honey points in each autonomous domain is dynamically adjusted, and joint modeling and dynamic optimization of a multi-organization honey array deployment strategy are realized on the premise of guaranteeing data privacy.

A cyber security system includes an importance node module to compute and use graphs to compute an importance of a node based on factors including a hierarchy and a job title of the user, aggregated account privileges from network domains and a level of shared resource access for the user. The graphs are supplied into an attack path modeling component to understand an importance of the network nodes and determine key pathways within the network that a cyber-attack would use, via a modeling the cyber-attack on a simulated and a virtual device version of the network. The cyber security system provides an intelligent prioritization of remediation action to a remediation suggester module to analyze results of the modeling the cyber-attack for each node and suggest how to perform intelligent prioritization of remediation action on a network node in one of a report and an autonomous remediation action.

The embodiment of the invention discloses a network access method and device, electronic equipment and a computer readable storage medium. According to the embodiment of the invention, when it is detected that the target application initiates the network access request, after the network access request is intercepted, the network configuration information corresponding to the target application is screened out from the preset network configuration information set; determining at least one domain name resolution mode corresponding to the target application and a resolution sequence of the domain name resolution modes, and according to the resolution sequence, performing domain name resolution on a network domain name address carried in the network access request by adopting the domain name resolution mode to obtain a target network protocol address of the target application, sending the target network protocol address to an application server of the target application, so that the application server performs network access based on the target network protocol address; according to the scheme, the access efficiency of network access can be improved.