4053 results about "Physical layer" patented technology

The invention discloses a cloud monitoring service operation and maintenance dynamic optimization system and method based on an AI intelligent agent, and relates to the technical field of cloud computing intelligent operation and maintenance. The method is used for solving the problems of hybrid cloud cross-layer data splitting, hidden fault association failure and operation and maintenance action conflict. Heterogeneous data of a physical layer, a virtual layer and an application layer are collected through a containerized probe, and a standardized cross-layer index is constructed through layered tagging and dynamic time sequence alignment. And constructing a fault propagation map through incremental correlation analysis and a dynamic time window, and identifying space-time coupling nodes. And based on the directional disturbance verification causal relationship, combining with the resource scheduling and fault chain incidence matrix fitting coupling degree index, and generating a root cause positioning instruction. And optimizing an action priority based on a propagation cost gradient and an asymmetric game strategy, and updating the model and the rule through a feedback closed loop. According to the invention, cross-layer data fusion and accurate fault positioning are realized, and the cloud service stability and the resource utilization rate are improved.

The invention discloses an information security management method based on data processing, and particularly relates to the field of information security management, comprising multi-source heterogeneous data acquisition, multi-dimensional feature index calculation, comprehensive threat detection calculation and adaptive threat decision. According to the method, the covert communication channel is accurately identified by constructing the encrypted traffic multi-mode detection model and combining protocol fingerprint entropy and traffic self-similarity analysis; an improved entropy weight fusion algorithm is adopted, collaborative analysis of system process abnormity, network behavior offset and hardware degradation is achieved, and a cross-dimension attack chain is reconstructed; a storage medium physical feature-cryptographic module runtime joint monitoring mechanism is created for the first time, hardware layer physical attacks and cryptographic side channel vulnerabilities are synchronously defended through temperature-delay correlation evaluation and key derivation density analysis, a complete attack surface from a physical layer to an application layer is covered, and the security is improved. And the detection precision and the response real-time performance of the complex threats are obviously improved.

The invention discloses a base station facility abnormity intelligent monitoring method and system, and the method comprises the steps: employing a multi-scale wavelet fusion pulse neural network to construct a dynamic signal perception topology according to the real-time data of a base station physical layer, and generating a space-time aligned base station full-dimension feature tensor; inputting the full-dimensional feature tensor of the base station into a fault mode confrontation distillation module, reconstructing a normal working condition manifold of the base station based on a physical constraint variational auto-encoder, and outputting an abnormal feature vector with a fault fingerprint identifier; fault propagation graph modeling is carried out on the abnormal feature vectors, and a base station fault root cause topological graph is generated in combination with back propagation credibility verification; and inputting the base station fault root cause topological graph into a toughness self-healing strategy generator, and finally outputting a base station facility self-healing strategy set meeting real-time constraint. By utilizing the embodiment of the invention, the accuracy and the real-time performance of abnormity monitoring can be improved, and the operation reliability and the communication service quality of the base station are improved.

The invention discloses an intelligent heat supply regulation and control system based on digital twinning and deep reinforcement learning. The system comprises a physical layer, a control layer and a control layer, wherein the physical layer is a physical heat supply system composed of heat source equipment, a transmission and distribution pipe network and a user terminal; according to the digital twinborn layer, a virtual heat supply system mapped with the physical layer in real time is constructed, the virtual heat supply system comprises a multi-physics field coupling model based on the thermodynamics and fluid mechanics principle, operation data of the physical layer are collected through a distributed sensor network, and the state vector of the virtual system is dynamically updated; and the intelligent decision-making layer is integrated with a DRL intelligent agent, the state space of the DRL intelligent agent is defined as a virtual system state vector output by the digital twin layer, the action space of the DRL intelligent agent is a regulation and control instruction combination of heat source power and pump valve opening, and a reward function fuses an energy consumption penalty term, a room temperature comfort reward term and a pipe network stability constraint term. According to the method, global optimization, high-precision continuous regulation and control and collaborative balance are realized through deep collaboration of digital twinning and deep reinforcement learning.

The invention relates to the technical field of synchronization in data communication, and provides a PTP protocol-based chip-level hardware timestamp generation method and system, and the method comprises the steps: 1, receiving a synchronization message and a delay request message from a main clock, carrying out the evaluation of a physical layer signal, and recording a first hardware timestamp; 2, responding to the received delay request message, generating and sending a delay response message, acquiring bidirectional transmission delay data by exchanging the delay request and the delay response message, and calculating clock skew in combination with the first hardware timestamp and the bidirectional transmission delay data; 3, adjusting the local clock frequency according to the clock skew; 4, after the synchronization is completed, associating the second hardware timestamp with the corresponding data message, and storing the associated data in a buffer area in the chip; and 5, generating standardized timestamp information, and outputting the standardized timestamp information through a chip interface. And high-precision time synchronization and timestamp generation are realized.

The invention discloses a message feature extraction method and related equipment, and relates to the technical field of feature extraction, and the method comprises the steps: obtaining original message data of target network flow and a corresponding physical layer signal waveform; analyzing the original message data based on a preset protocol layering rule, and determining a multi-layer protocol field set; determining a protocol layer feature vector based on the multi-layer protocol field set; determining a frequency domain feature vector based on the physical layer signal waveform; constructing a cross attention weight matrix based on the protocol layer feature vector and the frequency domain feature vector; and generating a target message feature based on the cross attention weight matrix. According to the method, through dual-mode deep fusion of protocol semantics and physical signals, the analysis capability of the features on encrypted traffic and protocol confusion attacks is enhanced, meanwhile, the feature robustness is improved through dynamic weight distribution and an anti-replay mechanism, and endogenous security features with high discrimination power are provided for complex network threat detection.

The invention relates to the technical field of abnormal state prediction, provides a multi-dimensional time sequence equipment abnormal state prediction method and system, and solves the problems of high false alarm rate and risk prediction inaccuracy in the prior art. The method comprises the following steps: collecting a multi-node operation state data set and communication transmission layer time sequence offset information of an equipment distributed system; jitter and delay association processing is carried out on the data, and a communication stability feature set is generated by quantizing space-time correlation of a jitter extreme value and delay fluctuation; obtaining physical layer deformation and temperature drift data of the communication cable, analyzing and generating a physical layer disturbance feature sequence based on optical signal feature offset, and converting the physical layer disturbance feature sequence into channel abnormal strength features; and cross-level feature coupling is carried out on the communication stability feature and the channel abnormal strength feature, and a communication node failure or data transmission abnormal risk is predicted based on a coupling result. According to the invention, millisecond-level linkage prediction of equipment-level physical disturbance and system-level communication risks is realized, the fault false alarm rate is reduced, and the cascade failure risk is blocked.

The invention relates to a secure communication method between an edge server and terminal equipment. The secure communication method comprises the following steps: establishing a physical layer channel state information database, generating a multi-dimensional feature vector and encoding the multi-dimensional feature vector into a terminal equipment identifier, generating an identity authentication request by the terminal equipment, and performing hash operation to obtain a first hash value; the identity authentication request and the first hash value are sent to the edge server, the edge server verifies the identity authentication request and queries a corresponding device key, performs hash operation to obtain a second hash value, generates an authentication response message after successfully comparing the second hash value with the first hash value, encrypts the authentication response message by using the device key, and sends the encrypted authentication response message to the edge server; and sending the encrypted authentication response message to the terminal equipment. And the terminal equipment decrypts by using the equipment key to obtain the session key, and communicates with the edge server based on the session key. By using the physical layer channel information and the equipment hardware characteristics, the security communication method fusing dynamic identity authentication and efficient key management improves the security, reliability and anti-attack ability of communication between the edge server and the terminal equipment.

The invention overcomes the constraints imposed by conventional wireless communication standards by introducing a physical-layer optimized architecture that decouples transmission control from any single protocol. Rather than being confined by the predefined behaviors of LTE, 5G NR, Wi-Fi, or NB-IoT, the system implements a unified control system that dynamically manages radio parameters—such as modulation, coding, and power—based on real-time link quality and network context. This cross-standard, multimode capability effectively supersedes traditional standard-driven implementations, enabling adaptive, low-latency, and spectrum-efficient communication in complex heterogeneous environments.The system dynamically controls radio access network (RAN) and physical layer parameters, including carrier aggregation, dynamic spectrum allocation, modulation and coding scheme (MCS) adaptation, beamforming configuration, channel coding, transmit power control, and frequency selection. The system architecture includes multi-mode base stations, relay nodes, and edge access points that support inter-RAT handover, fast radio link recovery, and seamless mobility across diverse wireless technologies.

The invention provides a data optimization processing method and system for edge calculation in architectural design. According to the method, geometric deviation and attribute change characteristics between building design models are obtained, and a version conflict identification graph for marking high-conflict areas is generated through topological relation comparison; deploying an incremental synchronous controller at an edge computing node of a physical layer, dynamically intercepting a high-conflict area association difference data fragment and compressing the high-conflict area association difference data fragment into an incremental data packet; analyzing a dependency topological relation between the models to predict a conflict propagation path; converting the path into a combined operation instruction conforming to a design rule through a collaborative modeling engine; and executing the instruction to integrate the difference, and outputting a conflict-free multi-building design integrated model after the models are fused. According to the method, second-level dynamic resolution and automatic fusion of building model conflicts are realized, the design iteration efficiency is improved, and the construction rework risk is eliminated.

The invention discloses a data flow optimization method and system based on artificial intelligence. The method comprises the steps of multi-modal data flow collection, digital twin basic modeling, decision enhancement, dynamic topology optimization and resource arrangement optimization. The invention relates to the technical field of network data flow management, adopts a data flow integration optimization scheme combining digital twin basic modeling, dynamic topological optimization and decision comprehensive optimization, not only improves the flexibility and real-time performance of a system, but also optimizes the efficiency and intelligent level of resource allocation; the quantum mapping and quantum optimization technology is adopted, adaptive noise and disturbance simulation are combined, the mapping precision and the dynamic adaptive capacity between a virtual layer and a physical layer are improved, and the state error between a virtual node and a physical node is optimized through quantum mapping parallel processing; hierarchical federated learning is combined with an adaptive learning strategy to optimize a data flow decision, and a joint optimization method of a quantum heuristic algorithm and a graph neural network is introduced into dynamic topological optimization.

The invention relates to a server cluster monitoring system based on multi-node collaboration and an implementation method thereof, a dynamic topology network module is configured to reconstruct a connection topology among monitoring nodes in real time according to node performance and link quality, support mixed configuration of a star type, a ring type and a net structure, and realize multi-node collaboration. Multi-dimensional data capture from a physical layer to an application layer is realized through a cross-level index acquisition module based on an integrated hardware sensor interface and a virtualization layer probe, and each node is enabled to perform collaborative reasoning through parameter encryption sharing through a decision model based on federated learning. A monitoring task fragmentation strategy is dynamically adjusted through an adaptive elastic fragmentation unit according to network delay and load fluctuation, and an abnormal event association rule base is updated in real time through an incremental knowledge graph construction unit. High availability and elastic expansion are realized through a multi-node collaborative architecture, the monitoring efficiency is improved in combination with dynamic load balancing and hybrid detection, and an intelligent multi-level response mechanism is constructed to guarantee the service continuity.

The invention discloses an adaptive modulation anti-multipath unmanned aerial vehicle swarm communication method and system based on MIMO-OFDM, and relates to the technical field of wireless communication, and the method comprises the steps: receiving a down-conversion baseband; synchronization and compensation are carried out; removing a cyclic prefix and carrying out fast Fourier transform; estimating a channel and noise on the training and pilot frequency, and correcting a common phase; performing frequency domain equalization and soft decision, forward error correction and cyclic redundancy check according to the estimation to obtain a control parameter, decoding a payload according to the control parameter, and performing statistics to form a link quality indication; modulating coding, bandwidth and spatial mode, configuring mapping, power and weight, and packaging physical layer protocol data; carrier sensing conflict avoiding sending, confirmation and retry are adopted to generate media access statistics; and the routing selects the next-hop multi-hop forwarding according to the transmission quality, and performs end-to-end statistics and recharge. Through cooperation of hierarchical synchronization and phase correction with cyclic prefix and FFT, crosstalk is suppressed, channel noise scale optimization soft decision is robust, data decoupling is controlled, and end-to-end availability is improved through multi-hop self-healing recharge.

The invention provides an adaptive interference suppression carrier communication system based on a complex electromagnetic environment, relates to the technical field of communication systems, and solves the problems that an existing communication system is poor in adaptability, weak in anti-interference capability and lack of collaboration and safety in the complex electromagnetic environment. The system comprises an environment perception module used for deeply perceiving an environment and identifying known and unknown interferences by using AI; the cognitive decision engine is used for generating a multi-domain control instruction by utilizing AI according to environment, internal, cooperation and safety states; the self-adaptive transceiving control module is used for executing cross-multi-domain parameter self-adaptive adjustment; the distributed collaborative module is used for realizing information sharing among nodes, federated learning and collaborative resource management; and the endogenous security enhancement module is used for executing active security mechanisms such as dynamic heterogeneous redundancy, mimicry defense and physical layer authentication. The invention further discloses a corresponding communication method. According to the method, the robustness, adaptability, efficiency and safety of a communication system in a complex electromagnetic environment can be remarkably improved.

The invention provides a property system virtual-real mapping inspection method, device and equipment based on digital twinning and a medium, and belongs to the technical field of property inspection. Real-time mapping of an equipment entity and a virtual model is achieved through layered design of a physical layer, a data layer, a twinning layer and an application layer; collecting static / dynamic data and reducing noise, and establishing a global coordinate system; constructing a 1: 1 parameterized model and binding equipment attributes; the state analysis model is used for evaluating the equipment health degree, and virtual-real identification and work order visualization are triggered when abnormity occurs; the inspection path is dynamically optimized, and the processing efficiency is improved in combination with AR assistance and dual-stage verification; and finally, updating the model weight and adjusting the inspection strategy through data-driven acceptance feedback. Real-time synchronization and intelligent decision making of the equipment state are realized, the inspection efficiency is improved, the fault omission ratio is reduced, the resource allocation is optimized, and the operation and maintenance transparency and reliability are enhanced.

The invention relates to the technical field of network security, in particular to a cloud data secure transmission system and method based on a quantum encryption technology. Comprising a quantum key generation and management unit used for generating a physical layer security key, realizing key true random generation through a quantum state unclonable principle, and optimizing key negotiation efficiency by adopting an improved adaptive basis vector matching algorithm; a data transmission encryption unit; a physical layer safety monitoring unit; and a channel fusion switching unit. According to the method, the physical layer security key is generated based on the quantum state unclonable principle, the dependency limitation of a traditional encryption algorithm on mathematics is broken through, and the cracking risk of quantum computing on bottom layer encryption logic can be reduced; according to the invention, photon polarization state parameters are collected in real time through the physical layer security monitoring unit, the eavesdropping behavior is detected based on the preset error rate threshold, real-time perception of the eavesdropping behavior in a transmission link is realized, and the defect that the security state of the physical layer cannot be perceived in real time in a traditional scheme is overcome.

The invention provides a seed packaging bag AI intelligent anti-fake traceability management system and method, and relates to the field of household kitchens. The AI intelligent anti-fake traceability management system for the seed packaging bag comprises an intelligent anti-fake packaging bag which is provided with a natural random physical texture layer, a dynamic optical structure layer covering the natural random physical texture layer and an encrypted identifier storing a digital identity (DID), and the microstructure of the natural random physical texture layer forms a uniqueness feature which cannot be copied. The dynamic optical structure layer generates a variable optical effect during physical interaction. Unique biological fingerprints are formed through microcosmic random textures of a packaging base material, the optical variable effect of a microlens array is overlaid, each packaging bag has the unclonability of the physical level, and in combination with dynamic comparison of a multi-mode AI engine on real-time texture features and block chain anchoring initial values and optical living body frequency analysis, the non-clonability of the packaging bag is improved. And a three-dimensional verification closed loop which is difficult to break by a counterfeiter is realized.

The invention provides a cross-protocol identification data intelligent analysis middleware method and system. The method comprises the following steps: taking multiple industrial communication protocol identifiers in advance to form a metadata set, and constructing a protocol feature element model library containing a non-standard protocol feature template; a programmable logic device is introduced, physical layer signal waveform characteristics are matched, and corresponding communication protocol stacks are dynamically switched at a hardware level according to a matching result; receiving a communication data stream through an electric domain processing unit of the programmable logic device, and generating a protocol analysis logic sequence in combination with a state transition rule of the meta-model library and a mode matching rule of the protocol stack; performing combined operation on the structured feature template and the analysis logic sequence to generate an executable cross-protocol data analysis rule; and when unknown protocol characteristics are detected, triggering dynamic reconstruction of the template, so that the analysis rule is adapted to a newly added protocol. According to the technical scheme provided by the invention, the protocol compatibility development cost in an industrial multi-protocol scene is remarkably reduced.

The invention discloses a high-voltage integration and cooperative control method and system for an energy storage system, and the method comprises the steps: carrying out the three-dimensional space coupling design of a high-voltage box and a power conversion system PCS through a topological optimization algorithm according to the power level and heat distribution demands of the energy storage system, and generating a physical layer architecture scheme of a high-voltage all-in-one machine; based on a physical layer architecture scheme of the high-voltage all-in-one machine, constructing a collaborative optimization data set by using a timestamp alignment technology; inputting the collaborative optimization data set into a model predictive control framework to generate dynamically adjusted PCS working parameters; and according to the PCS working parameters, the internal temperature distribution of the high-voltage all-in-one machine is calculated in real time through the three-dimensional thermal field reconstruction model, the rotating speed of a cooling fan and the switching frequency of a power device are dynamically adjusted, and a cooperative control instruction is generated. According to the embodiment of the invention, the integration level and the cooperative control capability of the high-voltage energy storage system can be improved, and the efficient and stable operation of the energy storage system is realized.

The invention discloses a server link fault positioning system and method, electronic equipment and a storage medium, and relates to the technical field of server link tests.Physical layer data and protocol layer data of a data collection point are collected through a collection assembly, a test assembly is controlled to conduct server link testing, the test assembly comprises a control module and an analysis module, and the control module is connected with the analysis module. The test instruction is issued to the server link through the control module, when the server link fault is monitored, the analysis module acquires the physical layer data and the protocol layer data of each data acquisition point from the acquisition assembly, and determines the fault position and / or the fault type of the server link according to the acquired data, so that the automatic link quality evaluation is realized, and the efficiency is improved. And the fault position and the fault type can be determined, so that the problems of difficulty in accurately positioning the fault position and distinguishing the hardware link fault and the software error through a single pressure test and low troubleshooting efficiency caused by manual fault positioning in the prior art are solved, and the technical effect of improving the troubleshooting efficiency is achieved.

The invention relates to the technical field of industrial distributed control system architecture, and discloses a dual-redundancy design method for a virtual controller VDPU, which comprises the following steps of: deployment of a four-network-port redundant network architecture: dividing four physical network ports into two groups of independent channels, and simultaneously configuring a network link automatic switching mechanism, the working states of the four network ports are monitored in real time, then double isolation of a physical layer and a protocol layer is achieved, and an independent heartbeat transmission channel is established; main / standby heartbeat monitoring and switching control: the main / standby controller periodically interacts state information packets through a special heartbeat channel, and establishes a three-level fault determination mechanism at the same time to perform seamless main / standby switching; a multi-mode data synchronization mechanism is implemented, namely initialization synchronization, increment synchronization during operation and exception recovery synchronization are started, separation of heartbeat signals and data synchronization can be realized through two groups of independent channels, and the fault-tolerant capability and the switching efficiency of the system are improved, so that the operation stability of the system is guaranteed.

The invention provides a 5G communication method and system based on environmental adaptation, and the method comprises the steps: fusing electromagnetic field intensity distribution, a terminal density thermodynamic diagram and obstacle reflection data through distributed sensing nodes, and generating a dynamic environment sensing matrix. Based on the matrix, establishing a beam pointing model of the motion trail of the user equipment cluster, dynamically adjusting the radiation direction of a beam main lobe, and creating a null region. And in combination with real-time channel multipath phase characteristics, non-uniform interval subcarrier distribution is reconstructed, and multipath phase compensation is carried out. A main lobe radiation direction and a subcarrier distribution mode are integrated into a physical layer structure, and the spatial multiplexing density of a time-frequency resource block is dynamically adjusted according to a service priority. And iteratively optimizing a collaborative matching threshold value of each parameter through closed-loop interaction of a forward channel response feature and a reverse control instruction. According to the invention, the anti-interference capability and the spectrum efficiency of the communication system are improved.

The invention discloses a bar code and RFID dual-mode fused tamper-proof data storage system, and relates to the field of data security storage, which comprises the following steps: uploading complete data to be stored into a scanning monitoring platform, splitting the data into static data and dynamic data, writing the static data into a bar code module, and writing the dynamic data into the bar code module; randomly distributed initial fluorescent particles are generated on the surface of the bar code data label through a scanning monitoring platform, a unique initial optical fingerprint is generated, if a bar code module is tried to be written or modified, the distribution position of the initial fluorescent particles is modified, an abnormal optical fingerprint is obtained, and an alarm is given; and writing the dynamic data into the RFID module, generating a dynamic key in each communication, and performing cross validation on the hash value based on the static data and the dynamic data. The method has the advantages that a three-dimensional protection system is constructed through a dual tamper-proof mechanism of a physical layer of fluorescent particle displacement and a password layer of a dynamic key in combination with cross validation of a hash tree, and the tamper-proof capability is improved.

The invention relates to the technical field of BMS and the like, and provides a battery management system based on adaptive digital twinning, a physical layer of the battery management system comprises a battery pack, a sensor network and an edge computing node, and is responsible for data acquisition and preprocessing; the digital twin layer comprises a self-adaptive multi-scale model and a real-time data engine, battery behaviors are dynamically simulated by coupling electrochemical, thermal and aging models, a future state trajectory prediction result is output, and the real-time data engine fuses sensor data, historical data and simulation data to drive model updating; the intelligent decision-making layer comprises a reinforcement learning controller and a fault prediction module which are deployed in a local server, the reinforcement learning controller dynamically optimizes a charging and discharging strategy according to a prediction result of the digital twinborn layer and issues and executes the charging and discharging strategy, and the fault prediction module analyzes multi-source time sequence data based on an LSTM network so as to early warn thermal runaway and short circuit risks in advance. According to the invention, long-term accurate mapping and adaptive adjustment between the battery physical entity and the digital model can be realized.

The invention discloses a digital twin autonomous optimization system based on building structure quality monitoring. According to the system, structure state data, environmental influence data, material performance data and historical record data are comprehensively collected through a multi-source data collection module; feature data such as a structure degradation rate and a material aging coefficient are extracted through an edge calculation preprocessing module; a digital twinborn body is constructed through a multi-layer fusion module, geometric layer fusion achieves crack grading labeling, physical layer fusion corrects parameters such as material elasticity modulus, and behavior layer fusion updates the structural damping ratio to reproduce dynamic behaviors. Outputting a structure health index, residual life prediction and maintenance suggestion through an autonomous optimization decision module; and in combination with a dynamic iteration updating module, the system is ensured to continuously adapt to the structure change through validity evaluation and parameter adjustment. The accuracy of building structure quality evaluation and the scientificity of maintenance decision making are improved, and the method is suitable for full-life-cycle management of various buildings.

A communication system that achieves reduction in delay time or the like at the time of mobility includes: a base station that is applied to a fifth-generation wireless access system; and a communication terminal that connects to the base station. When a cell that is a connection destination of a communication terminal in communication via any one of a plurality of cells constituted by the base station is changed, the base station transmits, to the communication terminal, setting information for measuring communication quality in a physical layer of the cell, the communication terminal measures the communication quality in another cell different from a cell being connected based on the setting information received from the base station, and transmits a measurement result to the base station, and the base station determines a cell to be a new connection destination of the communication terminal based on the measurement result.

The invention discloses a stamping equipment construction method based on digital twinning, and the method comprises the steps: firstly constructing a digital twinning system of stamping equipment, which comprises a physical layer, a digital layer, a virtual layer and an application layer; then, three-dimensional modeling and multi-physical-quantity simulation of the stamping equipment are carried out on a physical layer, and the real form of the equipment is reflected; real-time data acquisition and processing of the stamping equipment are carried out on the digital layer, a digital twin engine is constructed, virtual-real combination and real-time linkage processing are carried out on the virtual layer, and data analysis and optimization of the stamping equipment are completed; finally, man-machine interaction and visualization processing are carried out on an application layer, user interactivity and the intelligent level of equipment are improved, and intelligent decision support is carried out through data integration and dynamic adjustment. According to the stamping equipment construction method, high efficiency and intelligence of stamping equipment construction are achieved, the design period is remarkably shortened, the production efficiency and the equipment performance are improved, and meanwhile the cost and the operation and maintenance risk are reduced.

The invention discloses a multi-modal attack identification method fusing BMama and difference to guide trans-attention, which comprises the following steps: simulating a false data injection attack, a denial of service attack, an address resolution protocol spoofing attack and a domain name system spoofing attack, collecting physical layer sensor data and network layer flow data, and preprocessing multi-modal data; bMama is constructed to perform dynamic time modeling on multi-modal data, a graph neural network is combined to adversariate a variational auto-encoder, features of a power grid system topology and a communication topology structure are fused, and robustness of potential representation is enhanced through adversarial training; the method comprises the following steps of: guiding feature complementary fusion by using modal difference through a difference guide iteration cross-attention fusion mechanism, improving the capability of distinguishing complex attacks, finally carrying out attack detection and classification on fused modals, and executing end-to-end optimization according to a weighted combination of loss of each part. The method can effectively detect and classify the multi-modal attack in the smart power grid, and enhances the safety and reliability of a complex system.

The invention relates to the technical field of intelligent dormancy control of Internet of Things equipment, and discloses an intelligent dormancy control system of the Internet of Things equipment based on environment self-sensing, which comprises an environment feature extraction layer module, an environment dynamic model construction module, a self-adaptive dormancy decision engine module, a lightweight state cache module and a power supply cooperative control module. By acquiring the physical layer signal characteristics and the network layer connection state information of the NB-IoT protocol stack in real time, a dynamic model can be constructed based on the environmental signal fluctuation, the stability of the environment where the equipment is located can be accurately evaluated, the dormancy triggering condition can be dynamically adjusted, false wake-up caused by a fixed threshold value is avoided, dependence on a traditional sensor is reduced, and the reliability of the equipment is improved. The energy efficiency and adaptability of the equipment are improved, the anti-interference capability in an interference environment is improved, and the long-term stable operation of the equipment in a complex industrial environment is ensured.

The invention belongs to the technical field of network test equipment, and discloses network response test equipment and a test method thereof, and is characterized in that the network response test equipment comprises the following modules: a distributed multi-mode dynamic sensing probe used for capturing service flow characteristics and microsecond-level performance indexes of a network link in real time; the extensible data middle table is in data connection with the probe and is used for establishing a unified spatio-temporal index for cross-level performance data from a physical layer to an application layer; and the causal atlas analysis engine based on artificial intelligence is used for positioning a network fault root cause according to the cross-level performance data. According to the invention, an evaluation standard is automatically calibrated according to historical business load characteristics through an extensible data-in-station dynamic baseline threshold mechanism, so that a test environment completely fits complex scenes such as video burst frame transmission, database synchronization ACK, high-frequency transaction chain and the like, the simulation distortion of a traditional tool to business traffic burst and multi-protocol mixed characteristics is eliminated, and the test efficiency is improved. And the test result is ensured to accurately map the long-term stability requirement.