694 results about "Transport layer" patented technology

The invention provides a rail transit vehicle-ground security encryption control method based on a national cryptographic algorithm. The method comprises the following steps: realizing rail transit vehicle-ground security encryption control enabled by the national cryptographic algorithm by adopting a layered and segmented three-level security encryption architecture of a vehicle-mounted terminal layer-a network transmission layer-a core network layer; cooperative control of a national cryptographic algorithm is realized through three stages of terminal authentication, data encryption and tunnel encapsulation; in order to solve the problem of encryption interruption caused by wireless link switching such as 5G signal attenuation, the technical scheme of the patent realizes lossless switching through a three-layer linkage mechanism of signal monitoring, switching decision and key synchronization; self-adaptive intelligent adjustment of a key strategy is realized through a three-layer closed-loop architecture of environmental perception, intelligent evaluation and dynamic regulation and control; and the self-adaptive intelligent adjustment of the key strategy is realized through a three-layer closed-loop architecture of environmental perception, intelligent evaluation and dynamic regulation and control. And the national secret algorithm is combined with the block chain evidence storage technology to realize data tampering prevention, and the speed is high.

The invention discloses a bridge structure health state intelligent sensing and early warning system, relates to the technical field of bridge monitoring, and provides the following scheme that the bridge structure health state intelligent sensing and early warning system comprises a sensing layer, a transmission layer, a data layer, an analysis layer and an application layer which are connected in sequence and work cooperatively: the sensing layer is used for comprehensively collecting health state parameters of a bridge structure; according to the method, the comprehensiveness of monitoring parameters is guaranteed, the effectiveness and transmission efficiency of collected data are improved, redundant data are prevented from occupying resources, deep mining is achieved, a more scientific basis is provided for health status assessment and disease diagnosis, misjudgment caused by single parameter analysis is reduced, the diagnosis precision is improved, and the method is suitable for popularization and application. The intelligent optimization and simulation evaluation of the maintenance scheme are realized, the limitation of the traditional empirical scheme is avoided, the maintenance cost is reduced, the construction period is shortened, the influence on traffic is reduced, the performability of the scheme is improved, the stable and safe transmission of monitoring data in a complex environment is ensured, and the data loss or leakage is avoided.

The invention discloses a multi-channel high-precision water level dynamic real-time monitoring system for a drilling water pumping test, and the system comprises a sensing layer which is used for deploying a multi-source sensor array, inhibiting interference through distributed layout and electromagnetic shielding, collecting multi-dimensional data in real time, and carrying out the preliminary filtering; according to the transmission layer, an optical fiber and twisted pair redundant network is constructed, an EtherCAT protocol is adopted for low-delay transmission, AES-128 encryption tampering prevention is integrated, and edge nodes compress data and verify integrity; the processing layer is used for carrying out real-time preprocessing on edge calculation and switching a standby sensor in abnormal detection; the cloud end predicts the water level trend through Spark Streaming analysis and an LSTM model, distinguishes interference through a random forest algorithm, and outputs calibration data and an analysis report; the application layer is used for constructing a three-dimensional drilling model based on Unity, dynamically displaying water level changes, synchronizing a multi-parameter curve and supporting historical backtracking; the early warning module notifies abnormity through sound and light and short messages, the decision module generates a report and supports multi-drill-hole comparison, and the test strategy is optimized.

The invention provides a multi-stage desensitization electricity charge sensitive data protection system, belongs to the technical field of information security in the power industry, and relates to a full-life-cycle protection scheme of sensitive data such as an identity label, account information and contact information in an electricity charge service system. The problems that in the prior art, only simple masking or full-table encryption is carried out on a database layer, the desensitization dimension is single, multiple links are prone to leakage, no role fine-grained desensitization strategy exists, and exported files are difficult to trace are solved. The system comprises a data acquisition source and acquisition layer desensitization, a transmission layer encryption, a storage layer transparent encryption, an API gateway, a desensitization strategy center, a front-end dynamic mask, a watermark export, a log desensitization plug-in and an auditing log module, covers the whole process from data acquisition to log auditing, dynamically regulates and controls data display according to roles, and exports a file embedded identity watermark. And desensitizing the log and reserving operation marks. Full-link leakage prevention, fine-grained permission control and leakage traceability can be realized, and the transformation cost is low.

The invention relates to the technical field of edge computing, and discloses an edge computing intelligent decision-making system based on edge cloud collaboration, which comprises a terminal sensing layer, an edge computing layer, a network transmission layer and a cloud center layer. The terminal sensing layer is configured to collect original data; the edge computing layer comprises edge computing equipment, a resource scheduling module and a distributed synchronous triggering module which are respectively used for data preprocessing and model reasoning, dynamic resource allocation based on multi-agent deep reinforcement learning and multi-equipment synchronous acquisition realized through a precision time protocol; the network transmission layer dynamically adjusts a transmission strategy based on a reinforcement learning algorithm during data transmission; and the cloud center layer carries out training optimization on the model through a federal learning mechanism and issues the model to an edge side. According to the method, millisecond-level real-time intelligent decision making of an industrial site and sustainable evolution of the AI model are realized through a side cloud collaborative architecture, and the efficiency, the reliability and the self-adaptive capability of the system are effectively improved.

The invention discloses an electric power multi-protocol data conversion method and system based on object model dynamic mapping, and the method comprises the steps: receiving an original protocol message, recognizing a protocol type, extracting a logic name as a unique identifier of equipment, extracting an object identifier as a measurement point identifier, and extracting an electric energy array as a measurement point value; according to the protocol type and the equipment unique identifier, matching a corresponding object model template from a unified object model library; mapping the equipment unique identifier, the measuring point identifier, the measuring point numerical value and the acquisition timestamp obtained by analysis to corresponding fields in a template; and generating an object model data object conforming to a standard format, packaging the object into a message, executing an encryption authentication mechanism of a network layer and a transmission layer through the power Internet of Things security access gateway, and sending the message to an Internet of Things management platform. According to the invention, standardized, automatic and secure access of different protocol terminals is realized through protocol analysis and the unified object model library.

The invention discloses a network system security monitoring device, which comprises an intelligent sensing layer for scanning network traffic, logs and user behaviors by deploying AI-driven detection nodes; when a potential threat is detected, a structured alarm is generated immediately and pushed to a trusted transmission layer; the trusted transmission layer is used for generating a unique block identifier by adopting a Hash algorithm after the data integrity is verified through a consensus node; automatically triggering a repair process by using an intelligent contract; the self-adaptive decision-making layer is used for synchronizing configuration, flow and vulnerability states of physical equipment; after the vulnerability information is received, simulating various repair schemes in a virtual environment, evaluating the influence of the schemes on services, dynamically adjusting the priority, generating an optimal strategy, and pushing the optimal strategy to the automatic execution layer; the automatic execution layer is used for automatically executing and monitoring the repair progress through an agency-free technology after receiving the repair instruction of the self-adaptive decision-making layer, and triggering a rollback mechanism and generating a fault report if abnormity is detected; and after repairing is completed, a verification script is automatically generated.

The invention relates to the technical field of wireless communication, and discloses an interface protocol switching method and device, equipment, a storage medium and a product, and the method comprises the steps: obtaining state features between a transmitting end and a receiving end through a sensing layer, and collecting data information of a corresponding type according to the state features, the state features including a service feature, a network state and a server state; inputting data information into the intelligent decision layer, determining a switched transport layer protocol stack, and transmitting the transport layer protocol stack to a protocol execution layer; and switching the sending end and the receiving end to a transport layer protocol stack based on the protocol execution layer to perform data transmission. According to the application, the service features, the network state and the server state are dynamically perceived and extracted through the intelligent protocol adaptation system, the protocol stack of the optimal transmission layer is dynamically decided according to the extracted data, protocol requirements under different interaction scenes are adapted, and the flexibility and accuracy of data transmission are guaranteed.

The invention discloses a wire feeding processing intelligent operation and maintenance system based on cloud computing, and relates to the technical field of industrial automation and cloud computing. The problems that in an existing system, due to data transmission delay, abnormal response of equipment is not timely, system stability is affected by unreasonable computing resource scheduling, and the operation and maintenance effect is poor due to poor adaptability of a dynamic maintenance strategy are solved. Comprising an edge layer, a transmission layer, a scheduling layer, a cloud layer and an application layer. The edge layer collects data and makes an emergency response; the transmission layer optimizes data interaction based on network parameters; the scheduling layer balances task allocation through a deep reinforcement learning algorithm; the cloud layer constructs a prediction model and generates a dynamic maintenance strategy according to a result; the application layer visually displays and distributes operation and maintenance tasks; according to the method, the fault response speed, the resource scheduling balance and the maintenance strategy adaptivity are greatly improved, and the production continuity and the product quality are remarkably improved.

The invention discloses an AI-driven transport layer security protocol adaptive optimization system, which relates to the technical field of traffic data access and comprises a data access module, a state sensing module, a risk assessment module, an optimization transmission module and an adaptive encryption module. The data access module is used for capturing an original data flow from a network and a host in real time; the state sensing module is used for receiving the original data stream and setting a feature engineering state index; the risk assessment module is used for quantitatively assessing the safety score of the current state according to the current traffic environment state; the self-adaptive encryption module is used for constructing a password strategy library and generating an encryption configuration strategy according to a current traffic state; and the optimization transmission module is used for constructing a parameter intelligent optimization model and controlling algorithm interaction to generate performance scheduling optimization actions.

A method for authenticating an application program interface (API) invoker enhances secure communication between API invokers and a Common Application Program Interface Framework (CAPIF). The method involves sending authentication information from the API invoker to the CAPIF function, which authenticates the invoker's identity. The process includes obtaining enrollment information to establish a secure transport layer security (TLS) connection with the CAPIF function. Advanced authentication mechanisms leverage an authentication and key management for applications (AKMA) anchor key, enabling secure derivation and verification of application function keys (KAF). Additionally, the CAPIF function uses received authentication data to retrieve API invoker configuration information, onboard signing keys, and certificates. These elements facilitate secure API access and interaction while ensuring compliance with authentication protocols.

The invention discloses a traffic scheduling method and electronic equipment, and relates to the technical field of traffic scheduling, and the method comprises the steps: responding to a condition that a to-be-sent data stream accords with a transport layer protocol and the traffic size of the to-be-sent data stream is greater than a preset threshold value, and generating a plurality of candidate port values used for identifying the to-be-sent data stream at a data sending end; creating a plurality of detection data packets, wherein source port fields of the detection data packets are set as different candidate port values; sending the detection data packets to a data receiving end, and obtaining performance indexes of candidate network paths corresponding to the plurality of detection data packets based on the response of the data receiving end; determining a target source port value from the plurality of candidate port values based on the performance index; according to the embodiment of the invention, the source port field of the data packet corresponding to the to-be-sent data stream is modified into the target source port value, and the modified data packet corresponding to the to-be-sent data stream is sent to the data receiving end, so that the technical problem of load imbalance of a multi-path network in related technologies is solved, and the reliability of traffic scheduling is improved.

The invention discloses a multi-protocol adaptive Internet of Things device communication management method and system, and relates to the technical field of Internet of Things device communication management, and the method comprises the steps: capturing an original message sent by a source device through a communication management node disposed at an edge side when an Internet of Things device initiates a communication request, obtaining a source device identifier, a target address and a transport layer protocol type of the original message; identifying a used application layer protocol according to the structural features and the communication context of the original message, extracting an operation intention contained in the original message, and generating a standardized semantic feature vector; on the basis of the difference degree between the standardized semantic feature vector and semantic feature vectors of other protocols, initial compatibility scores among the protocols are determined, and a communication topological graph is constructed in combination with real-time delay and node resource states of network links; and continuously recording communication execution results of different protocol pairs on each node, and generating a dynamic memory factor according to the change trend of the execution results.

The invention relates to the technical field of system control, in particular to a bionic neuron dynamic topology CAN system which comprises a control layer and a transmission layer, the transmission layer is connected with the control layer, and a dynamic rate domain is arranged in the transmission layer and used for achieving seamless connection and data interaction between different rate domains; the execution layer is connected with the transmission layer and the control layer, and the execution layer comprises a plurality of neuron nodes; and the fault-tolerant layer is connected with the control layer, a topology self-healing protocol is arranged in the fault-tolerant layer, and the fault-tolerant layer is used for monitoring the running state and fault information in real time, predicting the fault occurrence probability and implementing a corresponding strategy. According to the invention, a special architecture comprising the central coordinator, the dynamic rate domain and the neuron nodes is constructed, and efficient, safe and reliable operation of the system is realized.

Aspects of the subject disclosure may include, for example, deploying a reverse proxy server in front of a first type of web servers and a second type of web servers, where the first type of web servers is compliant with a current version of payment card industry data security standard (PCI DSS) and supports a first version of a transport layer security (TLS) protocol, and where the second type of web servers supports one or more TLS protocols that are older than the first version of TLS protocol, detecting, using the reverse proxy server, a TLS protocol version used in an incoming request, and determining, using the reverse proxy server, routing of the incoming request to one of the first type of web servers and the second type of web servers at least based on the detected TLS protocol version. Other embodiments are disclosed.

The invention provides an intelligent inspection system based on a robot and a camera, and relates to the field of intelligent manufacturing, the system adopts a four-layer architecture including a sensing layer, a transmission layer, a platform layer and an application layer, the sensing layer is composed of a fixed camera and an intelligent inspection robot; the transmission layer adopts optical fibers and 5G hybrid networking; the platform layer is integrated with a distributed server cluster, a data platform and an AI inference engine; the application layer provides a Web and mobile terminal management interface. The core of the system adopts a plurality of AI algorithms, including an instrument reading recognition algorithm based on Hough transform and CRNN, a leakage detection algorithm combined with background difference and an optical flow method, and a multi-device collaborative scheduling algorithm based on reinforcement learning, and constructs a digital twinborn inspection scene of virtual-real mapping. According to the invention, automatic and intelligent inspection and visual monitoring of power plant instruments, pipelines, power distribution rooms and other areas are realized, the inspection efficiency and accuracy are effectively improved, and the labor cost and the safety risk are reduced.

Embodiments of the present disclosure provide a scheduling method and system, a service device, a computer program product, and a storage medium. For a connection establishment request in a transport layer, a new scheduling mechanism is provided in a kernel mode of an operating system in the service device. In the kernel mode, in response to receiving the connection establishment request for a target application, a process list corresponding to the target application can be acquired, wherein the process list comprises at least one candidate process determined by performing preliminary screening on the basis of the running states of user-mode processes. In this way, by means of the process list, the kernel mode can indirectly sense the running state of each user-mode process as a scheduling basis, and can schedule the connection establishment request to a target process in the process list, so as to process the establishment request by means of the target process. Accordingly, in the kernel mode, the connection establishment request can be scheduled to a user-mode process whose running state better meets the requirements of an application scenario, so that the running states of the user-mode processes are more balanced, thereby improving the performance of service devices.

The invention discloses an elevator internal device fault intelligent inspection management system and management method. The system comprises a sensing layer, a transmission layer, a platform layer and an application layer which communicate in sequence. The sensing layer collects operation data of devices such as an elevator traction machine and a portal crane system through special sensors such as a vibration sensor and a temperature sensor and a camera. The transmission layer encrypts transmission data in a mixed transmission mode after edge calculation preprocessing; the platform layer adopts double databases to store data, and fusion analysis is performed through a convolutional neural network model and a long-short-term memory network model; the application layer provides exclusive functions for multiple subjects. The management method forms a closed loop through data acquisition, processing, diagnosis, operation and maintenance. According to the method, the fault identification accuracy is over 96 percent, the response time is shortened to be within 30 minutes, 45 percent of sudden faults are reduced, accurate decision is supported, the safety is improved, the operation and maintenance cost is reduced, and the applicability is high.

The invention relates to a digital twin-driven distributed warehousing system and method, and belongs to the technical field of intelligent logistics. The system comprises a sensing execution layer, a network transmission layer, an edge computing layer, a cloud platform layer and an application service layer. The method comprises the following steps: acquiring storage physical entity data through a perception execution layer; the data is transmitted to the edge computing layer and the cloud platform layer through the network transmission layer; in the cloud platform layer, a high-fidelity virtual warehouse is constructed and synchronized through a digital twin engine; using a multi-agent reinforcement learning algorithm to perform centralized training in a digital twin environment to generate a distributed cooperative scheduling strategy; and issuing the strategy to an edge computing layer and a sensing execution layer, and driving an autonomous mobile robot cluster to execute a cooperative task. According to the invention, step-type improvement of the warehousing system in flexibility, intelligence and cooperative capability is realized, and the problems of rigid bottleneck, non-optimal decision and low cooperative efficiency of a traditional system are solved.

The invention discloses a multi-protocol compatible hydropower station field bus photoelectric signal synchronous acquisition device and method, and relates to the technical field of industrial bus testing, the device comprises a core control layer, a signal conditioning layer, a photoelectric interface layer, a clock synchronization layer, a power management layer and a data storage and transmission layer; the core control layer adopts a dual-core framework of a domestic Loongson 2K0300 main control unit and a domestic FPGA (Field Programmable Gate Array) time sequence control unit; the clock synchronization layer adopts a two-stage synchronization mechanism of'local crystal oscillator time sequence control + NTP network clock calibration '; and the signal conditioning layer is integrated with a multi-protocol self-adaptive conditioning module and an industrial-grade anti-interference module. The method comprises the steps of clock initialization and calibration, parameter configuration, photoelectric signal parallel acquisition and time sequence synchronization, and data preprocessing and transmission, so that synchronous acquisition of six types of bus protocol photoelectric signals is realized. The system has the advantages of multi-protocol compatibility, autonomous controllability, good portability and the like, and provides reliable data support for bus communication quality evaluation and fault diagnosis.

The invention discloses a circular region quantum communication channel redundancy configuration system based on AI-block chain collaboration. The system comprises a quantum transmission layer, an AI optimization layer and a block chain layer. The quantum transmission layer is based on a circular area sensor network topology, and comprises a central node, a quantum relay ring and a sensor node; the quantum transmission layer adopts ring topology, a center node is located at the center of a circle, and relay nodes are uniformly distributed according to polar coordinates; bidirectional quantum communication is realized between the sensor node and the central node through a quantum relay ring; the AI optimization layer comprises a channel state sensing module, a quantum graph neural network module, a QoS analysis module, a service priority mapping module, a dynamic scoring engine and a resource arbitration module; the block chain layer constructs a dynamic trust center to form an evaluation-evidence storage-control closed loop. According to the invention, the problems of limited transmission distance, high equipment cost, low key distribution efficiency and low resource utilization rate of quantum communication in a circular area scene are solved.

A quantum-resistant security enhancement method for a transport layer security protocol, comprising: (011) acquiring a first quantum key and a quantum key identifier from a serving node; (012) performing post-quantum cryptographic encryption on the quantum key identifier to obtain a first encryption result, and sending the first encryption result to a network device; (013) decrypting a received second encryption result to obtain a second decryption result; (014) obtaining a first terminal handshake key and a first network device handshake key on the basis of the first encryption result and the second decryption result; and (015) generating a second terminal handshake key and a second network device handshake key on the basis of the first quantum key, the first terminal handshake key, the first network device handshake key, the first encryption result and the second decryption result, so as to encrypt communication between the terminal and the network device.

The micro-service processing system provided by the embodiment of the invention comprises an event identification module which is used for defining a business domain event type and registering an event attribute structure; the event bus module constructs a distributed communication network containing a dual-channel message queue, and the event bus module implements partition routing according to event types; the event processing module is composed of an event producer and a consumer which are executed asynchronously, the event producer packages service actions into a standardized event data packet, and the consumer processes subscription events through a thread pool; the event storage module adopts a hierarchical log database for persistence of an event sequence and supports reestablishment of a service state according to a timestamp; and the security control module is used for implementing service authentication and event content encryption on a transmission layer. Through event bus dual-channel design, sender box transaction binding and hierarchical storage optimization, millisecond-level event processing delay is realized while the reliability of distributed transactions is ensured, and second-level state recovery can be realized based on a complete event log when a service fault occurs.

The invention relates to the technical field of digital information transmission, and discloses an aircraft multi-network fusion data real-time transmission and distribution system which comprises a physical layer state monitoring module, a transmission quality deduction engine, a deduction routing engine and a mapping model calibration module. Deducing a transmission quality index based on the transmission layer-physical layer mapping model so as to guide a routing engine to distribute data packets; meanwhile, the calibration module utilizes actual transmission layer feedback of a data packet to dynamically correct the mapping model, active measurement is replaced by passive deduction, information lag and resource occupation are avoided, and the problem of drifting failure of a deduction model in a complex environment is solved by introducing a self-calibration closed loop.

There is provided a method at a network node of a communication network, comprising: receiving an uplink reference signal from a user equipment; estimating, based on the received uplink reference signal, delay information regarding a delay profile of a communication channel between the user equipment and the network node and spatial information regarding the communication channel; applying both the delay information and the spatial information in precoding of at least one downlink reference signal; transmitting the at least one precoded downlink reference signal to the user equipment; and receiving, from the user equipment as a response to the transmission of the at least one precoded downlink reference signal, channel information, the channel information indicating at least non-zero coefficients of at least one channel transmission layer.

The invention relates to the technical field of communication, in particular to a transmission layer ultra-low delay congestion control method assisted by physical layer information. The core of the method is as follows: a sending end continuously acquires physical layer channel quality information and predicts a future channel capacity change trend based on historical and current information sequences; and then, dynamically calculating and smoothly adjusting the size of a transmission layer congestion window through a predefined mapping relation according to a prediction result, actively reducing the window before predicting that the channel is deteriorated, and timely increasing the window when the channel is improved. In addition, the method also comprises a fault-tolerant mechanism, and automatically switches to a traditional congestion control mode when the prediction is misaligned by monitoring the deviation between the prediction and the reality. Through cross-layer information utilization and prospective control, the method aims to effectively reduce data transmission delay and jitter and improve the capability of a network to cope with channel dynamic changes and the overall stability.

The invention relates to the technical field of electric power internet of things, in particular to a cloud-side collaborative intelligent gateway. The method comprises the following steps: a high-frequency data acquisition and packaging unit acquires voltage and current waveform data; the equipment compatibility and data intercommunication unit adopts a multimode transmission layer decoupling design, and performs protocol conversion and data standardization through butt joint with electrical equipment; an edge intelligent analysis unit extracts frequency spectrum features of original voltage and current waveform data at a gateway end by using FFT (Fast Fourier Transform), introduces a lightweight convolutional neural network model to identify the operation state and abnormal features of the electrical equipment, and judges the type of the electrical equipment in combination with a load feature library; the data compression and transmission unit compresses, packs and encrypts the voltage and current waveform data, adds CRC32 verification, and then uploads the data to the cloud. According to the invention, a high-frequency double-cycle sampling mechanism and a high-precision coding mode are adopted, so that the capturing capability of high-frequency harmonic waves and transient disturbance in voltage and current waveforms is remarkably improved.

The invention discloses a remote intelligent control system and control method for a crane, and relates to the technical field of crane control, the system comprises the following components: a physical entity layer, a digital twinborn layer, a 5G transmission layer, a VR interaction layer and a virtual-real calibration layer; according to the method, an equipment state predictive modeling technology is adopted through a digital twinborn layer, historical operation data of a crane are collected, an equipment state database is constructed, key features related to equipment faults are extracted, and an equipment state prediction model is constructed based on a long-short-term memory network; according to the method, the change trend of equipment state parameters in the future 72 hours can be predicted, when the predicted state parameters approach or exceed a fault threshold value, the system can automatically mark corresponding parts in the digital twin, generate maintenance suggestions and synchronize the maintenance suggestions to a VR interaction layer to prompt an operator, and the maintenance suggestions are displayed in the VR interaction layer. According to the predictive maintenance mechanism, equipment faults can be early warned and processed in advance, the non-planned downtime is shortened, and the operation and maintenance cost is reduced.

Methods and devices for supporting authentication of a first Transport Layer Security (TLS) device, wherein a second TLS device receives from the first TLS device a message indicative of the credential type that the first TLS devices will provide to be authenticated, i.e., Verifiable Credential (VC)-based certificate. The second TLS device then receives, from the first TLS device, a first VC and a first Verifiable Presentation (VP) proof which the second TLS device uses for authenticating the first TLS device.

The application relates to an anti-quantum password migration method, system, electronic equipment and storage medium, and belongs to the technical field of anti-quantum data transmission. The method comprises the following steps: adaptively extending a transmission layer security protocol; and performing secure transmission of application data by an encryption end and a decryption end based on the extended transmission layer security protocol, wherein the secure transmission process of the application data comprises the following steps: respectively generating a master key, a multi-level sub-key and a path key chain based on an extended password suite according to a chained post-quantum key generation mechanism; generating an encryption key by the encryption end using part of the sub-key, encrypting the application data in a symmetric encryption mode to generate ciphertext, and sending the ciphertext and a path node key at the end of the path key chain to the decryption end; verifying the path node key by the decryption end, generating a decryption key by the decryption end using part of the sub-key after the path node key is verified, and decrypting the ciphertext. The application realizes the security and high efficiency of data transmission in the anti-quantum password migration process.