174 results about "Sequence matching" patented technology

The invention discloses a data security dynamic evaluation system and a protection method, belongs to the technical field of information security, and is used for solving the problem of terminal equipment access control and behavior risk dynamic collaborative protection. The method comprises the following steps: generating fingerprints through terminal equipment features, verifying authorization, inputting access feature slices into a time sequence model by authorized terminal equipment, generating a trust score based on cosine similarity of a behavior sequence and a prediction sequence, and constructing a Markov model to dynamically select an authentication mode according to the trust score; calculating a risk index by combining network and geographic information, and distributing the risk index to a real or virtual environment; and the unauthorized terminal equipment distributes the virtual environment after registration. Differentiated monitoring is carried out, a time sequence library is established in the virtual environment, and doubt scores are generated through sequence matching; the state deviation of the real environment is calculated through a hidden Markov model, and the risk score is generated by fusing the multi-dimensional features. And based on the result management authority, the suspicion terminal equipment isolates and shrinks the authority, the compliance terminal equipment authenticates and migrates, and the access is regulated and controlled according to the minimum privilege principle and the time window mechanism.

The invention provides a network attack detection method and system based on a distributed intelligent probe, and the method comprises the steps: receiving real-time flow data synchronously collected by the distributed intelligent probe at each node of a network, carrying out the inter-node interaction relation modeling processing of the real-time flow data, recognizing a flow communication mode between different network nodes, and carrying out the detection of the network attack. Generating a flow association map containing the node connection relationship and the communication frequency; carrying out abnormal communication path mining based on the flow association map, and extracting a node communication sequence with an abnormal mode by analyzing the deviation degree of a node connection relationship and the fluctuation characteristics of communication frequency; performing pattern matching processing on the node communication sequence and an attack behavior template in a preset attack feature library, calculating sequence matching similarity and generating an attack matching degree score set; and determining a network attack type and attack source node positioning information, and generating a network attack detection result. According to the invention, the practicability and effectiveness of network attack detection are improved.

The invention relates to the technical field of occupational simulation training evaluation, and discloses a system for college student occupational scene simulation training evaluation. The system comprises a task analysis unit, a dynamic behavior modeling unit, a multi-mode interaction management unit, a state evolution tracking unit, a strategy adaptation unit and a comprehensive evaluation generation unit. The system receives the initial scene description and generates a structured task framework, and behavior parameters are configured for student roles; constructing a multi-modal interaction atlas by fusing aligned voice, action and sight line data in real time; identifying a key decision node, and dynamically tracking a team state evolution path; matching and adjusting strategies in a behavior rule base according to the evolution sequence, and outputting an adaptive intervention scheme; and finally generating a multi-dimensional structured evaluation report. According to the system, deep insight and dynamic and objective intelligent evaluation of complex interaction behaviors in the simulation training process are realized.

The invention relates to the technical field of traffic event identification, and discloses an abnormal traffic event identification method and system based on a traffic large model, and the method comprises the steps: obtaining a traffic data flow, extracting an abnormal feature vector, and obtaining an abnormal signal candidate set; grouping the candidate sets and calculating a deviation degree, and if the deviation degree exceeds a threshold value, taking the deviation degree as a risk signal to form an input subset; environment variables are extracted from the subsets, a mapping relation is established, and anomaly recognition embedding representation is obtained; classifying the embedded representation, judging a congestion precursor and generating an early warning signal to obtain an early warning signal sequence; matching the sequence to obtain an abnormal event chain; if the integrity is higher than a threshold value, analyzing the type to obtain an abnormal event type; extracting a correlation feature vector from the type, pushing the correlation feature vector to a traffic management platform to obtain an instruction, and obtaining an emergency response trigger instruction sequence; and executing the instruction sequence to extract a feedback data stream, inputting the traffic large model to judge the accuracy rate, and if the judgment accuracy rate is met, determining an optimized anomaly recognition framework. The method can solve the problem of insufficient early warning capability.

Compressing files is disclosed. An input file to be compressed is first aligned. Aligning the file includes splitting the file into sequences that can be aligned. When splitting the file into sequences or when performing subsequent recursive splitting, the splitting is based on a longest sequence match. The result is a compression matrix, where each row of the matrix corresponds to part of the file. A consensus sequence is determined from the compression matrix. Using the consensus sequence, pointer pairs are generated. Each pointer pair identifies a subsequence of the consensus matrix. The compressed file includes the pointer pairs and the consensus sequence.

The invention discloses a VR / AR martial art teaching method, device and equipment based on dynamic time warping and a computer readable storage medium. The method comprises the steps of obtaining a user skeleton point sequence corresponding to a user action and a standard action template; determining a specific weight coefficient of the joint for comparison processing; comparing the user skeleton point sequence with a standard action template based on a specific weight coefficient of a joint by applying a weighted dynamic time warping algorithm so as to generate an optimal warping path; obtaining a sequence matching score and a posture matching score according to the optimal regular path and the key force generation event sequence; inputting the sequence matching score, the posture matching score and the determined existing force application sequence error and / or action posture error into a language generation type model to generate a text feedback instruction; and based on the text feedback instruction, generating and displaying immersive teaching feedback in a VR or AR environment. The method has the advantages of multi-dimensional evaluation, immersive feedback and the like.

The invention discloses a network traffic prediction method based on periodic decomposition and similarity matching, and relates to the technical field of time sequence prediction, and the method comprises the steps: S1, collecting network traffic historical data; s2, extracting a time period from the network traffic historical data sequence through fast Fourier transform, and segmenting the network traffic historical data sequence into a plurality of periodic subsequences and a to-be-predicted sequence; s3, clustering all the periodic subsequences based on the dynamic time stretching distance to obtain a median subsequence capable of representing each class of features; s4, matching a median sequence with the highest similarity with the to-be-predicted sequence as a reference median sequence; and S5, based on the reference median subsequence, predicting the residual sequence value of the to-be-predicted sequence by using an energy amplitude ratio method. According to the method, subsequence matching is carried out by utilizing the periodicity and similarity of the network traffic, the data change in a short period can be accurately predicted, a complicated parameter selection process is not needed, and thus the prediction efficiency of the network traffic is improved.

The invention provides a control method and a control device of an underwater robot. The control method of the underwater robot comprises the following steps: establishing an underwater robot system model; performing obstacle avoidance path planning by using a sampling algorithm to obtain a discrete geometric path point set connecting the starting point and the ending point; a full-state reference sequence matched with the control method underwater robot system model is generated based on the control method discrete geometric path point set; constructing a cost function for trajectory optimization based on the control method underwater robot system model and the control method full-state reference sequence; generating an initial control sequence and an initial state sequence according to the deviation between the current state of the underwater robot in the control method and the full-state reference sequence in the control method; and performing iterative optimization by taking the control method cost function as an optimization target and taking the initial control sequence and the initial state sequence of the control method as hot start initial values to obtain a control instruction sequence of the underwater robot of the control method.

The invention relates to the technical field of heterogeneous computing power allocation, in particular to a heterogeneous computing power dynamic allocation method based on big data analysis, which comprises the following steps: analyzing a source, a target, a type and dependency of a data task, normalizing parameters and extracting features, identifying a key task, combining a computing power resource queue and historical scheduling efficiency, optimizing an allocation state, and allocating the heterogeneous computing power according to the allocation state. And screening the computing power resources which run normally, analyzing the dominant frequency temperature and response performance, adjusting the distribution relation, and forming a dynamic distribution sequence. According to the method, standardization, normalized mapping and feature aggregation are carried out on the data task multi-dimensional labels, deep mining and classification of task features can be achieved, dynamic linkage of task requirements and computing power resource states is completed according to big data analysis, relevance between the tasks and heterogeneous computing power resources is finely quantified, and the method has the advantages of being simple in structure, convenient to operate and high in efficiency. And in combination with a resource response expression and grading mechanism, a task allocation strategy is automatically adjusted, and the resource adaptation degree and allocation sequence matching during task processing are guaranteed.

The invention provides a memory parking repositioning method and device, electronic equipment and a storage medium, and in the method, a continuous path is decomposed into a plurality of topological path segments, so that a complex continuous space positioning problem is converted into a discrete path segment sequence matching problem, and the positioning accuracy is improved. Complexity and calculation amount of subsequent positioning search are greatly reduced, cost is low, in addition, when it is recognized that the vehicle enters the next topological path section from one topological path section, the database is inquired to obtain the starting point pose of the new topological path section, the starting point pose of the new topological path section is directly used for resetting the pose of the vehicle subjected to track plotting, and therefore the accuracy of track plotting of the vehicle is improved. According to the method, when a vehicle runs in a topological path section from zero, the transverse distance from the vehicle to the reference path of the current topological path section is measured according to a preset interval, and the pose of the vehicle is subjected to filtering correction, so that the effects of regular zero clearing of a large error and real-time suppression of a small error are achieved; and high precision of full-path relocation is ensured.

The invention provides a radar ranging interference echo filtering method, a laser radar and a readable storage medium, and relates to the technical field of laser radars. The method comprises the following steps: driving a laser radar to emit a multi-detection pulse coding sequence in a current distance measurement period, and performing pulse sequence construction on all echo pulses received in the current distance measurement period to obtain at least one echo pulse sequence to be matched; wherein the total number of echo pulses of each to-be-matched echo pulse sequence is consistent with the total number of detection pulses of the multi-detection pulse coding sequence, and then pulse distribution characteristic matching is carried out on each to-be-matched echo pulse sequence and the multi-detection pulse coding sequence, so that all the echo pulses received in the current distance measurement period are subjected to pulse distribution characteristic matching; and a target echo pulse sequence successfully matched with the multi-detection pulse coding sequence is screened and reserved, so that over-period echo interference and multi-radar echo interference in the laser radar ranging process are removed, and the laser radar ranging accuracy is improved.

The invention discloses a text matching positioning method, system and device and a medium. The method comprises the steps of obtaining an original long text and segmenting the original long text into ordered text blocks; selecting the first N text blocks to form a first candidate set based on the common substring sorting of the to-be-matched text and each text block; intercepting the first candidate set according to head and tail characters of the to-be-matched text to obtain a second candidate set; calculating similarity scores of the text blocks in the second candidate set and the to-be-matched text through a sequence matching similarity algorithm; combining the scores with the first candidate set to determine a matching result and output a position, and judging that no matching exists when all the scores are lower than a preset minimum threshold value. According to the method, the limitation of a traditional matching mode is broken through through primary screening of common substrings, accurate interception of head and tail features and multi-layer processing of a sequence matching similarity algorithm, complex scenes such as text missing and semantic equivalent expression can be effectively handled, the accuracy and robustness of text positioning are improved, and the user experience is improved. The method can be widely applied to the fields of document management, information retrieval, academic analysis and the like.

The invention discloses a lossless compression storage method and system based on heterogeneous data in a credential environment, and the method comprises the steps: firstly, extracting a mapping relation between a file type and a structural feature through scanning a target file, carrying out the preliminary lossless compression after classification and grouping, and further employing a sliding window matching and sequence matching algorithm to optimize compressed data for a redundancy mode, and then generating a metadata structure containing a check code and a compression parameter, packaging the metadata structure into a data packet supporting cross-platform transmission, finally transmitting the data packet to a target storage device through a secure write-in protocol, and verifying data consistency and recovering path feasibility by using the check code. According to the method, the data compression efficiency is remarkably improved, the compatibility of cross-platform transmission and the integrity of stored data are ensured, and efficient and reliable technical support is provided for complex electronic file processing.

The invention relates to the technical field of residual current protection, in particular to a power distribution network residual current protection method and system based on a distributed photovoltaic power supply, and the method comprises the following steps: obtaining a zero-sequence current waveform in a disturbance period, recognizing an abrupt change node, analyzing the fluctuation rhythm and trend, and constructing a response structure; the method comprises the following steps: extracting a sequence relationship between abrupt change nodes and fluctuation rhythms, constructing a response fragment set with trend consistency and rhythm coherence, screening response fragments capable of triggering protection, adjusting a starting point and a sequence, completing action triggering rhythm merging, and generating a residual current protection strategy, in the method, through sequence relationship extraction between the abrupt change nodes and the fluctuation rhythms, constructing a response fragment set with trend consistency and rhythm coherence, and combining a change cooperation relationship between sections; key paragraphs capable of triggering protection are screened out, the triggering sequence and the starting point position are adjusted according to trend continuity, the starting time sequence matching degree is improved, behavior stability is judged through trend coherence, rhythmic merging of response structures is achieved, action strategies with directivity and continuity are output, and the precise control capacity of protection response under variable disturbance is enhanced.

The invention provides an airport security check passenger flow volume prediction method and system, electronic equipment and a storage medium, and is applied to the technical field of airport security check. Target historical airport security check queuing data before target time is acquired; fusing the queue information of each target historical queue to obtain fused queue information of a target fused historical queue; performing empirical mode decomposition processing on fusion queue information of the target fusion historical queue to obtain a plurality of target data sequences and target residual components; determining a prediction model matched with the target data sequence, and performing airport security check passenger flow prediction according to the target data sequence or the target data sequence and the target residual component through the prediction model matched with the target data sequence to obtain a target prediction result; and determining the airport security check passenger flow volume corresponding to the target time according to each target prediction result, thereby being capable of adapting to unstable data, meeting actual requirements, and improving the accuracy of predicting the airport security check passenger flow volume at the same time.

The application discloses a lossless compression storage method and system based on heterogeneous data in a Xinhua environment, first extracts the file type and structure feature mapping relationship by scanning the target file, classifies and groups, and then carries out preliminary lossless compression, further adopts a sliding window matching and sequence matching algorithm to optimize the compressed data for the redundant mode, then generates a metadata structure containing a check code and compression parameters, encapsulates into a data packet supporting cross-platform transmission, finally transmits to the target storage device through a secure write protocol, and verifies the data consistency and recovery path feasibility by using the check code. The application significantly improves the data compression efficiency, ensures the compatibility of cross-platform transmission and the integrity of storage data, and provides efficient and reliable technical support for complex electronic file processing.

The present invention makes it possible to eliminate inconsistency between an atlas bit stream and a displacement amount bit stream. In a mesh decoding device 200 according to the present invention, a mesh reconfiguration unit 206 includes: a syntax matching unit 206A configured to generate and output a matching basic mesh, a matching coefficient sequence, a matching displacement amount vector number, and a matching subdivision frequency by using an atlas, a basic mesh, a coefficient sequence, a displacement amount vector number, and a subdivision number; a sub-mesh reconfiguration unit 206B configured to generate and output a sub-mesh sequence using the matching basic mesh, the matching coefficient sequence, the matching displacement amount vector number, and the matching subdivision number; and a sub-mesh combining unit 206C configured to generate and output a single mesh by combining the sub-mesh sequences.

The application relates to the technical field of residual current protection, in particular to a power distribution network residual current protection method and system based on a distributed photovoltaic power supply, which comprises the following steps: acquiring a zero sequence current waveform in a disturbance period and identifying a mutation node, analyzing fluctuation rhythm and trend to construct a response structure, screening a response fragment capable of triggering protection and adjusting a starting point and sequence, completing action trigger rhythm merging, and generating a residual current protection strategy; in the application, a response fragment set with trend consistency and rhythm continuity is constructed through sequence relationship extraction of the mutation node and the fluctuation rhythm, key paragraphs capable of triggering protection are screened in combination with change coordination relationship between sections, the trigger sequence and starting point position are adjusted according to trend continuity, the starting time sequence matching degree is improved, behavior stability is judged through trend continuity, rhythm merging of the response structure is realized, an action strategy with directionality and continuity is output, and the precise control ability of protection response under variable disturbance is enhanced.

This application provides a game testing method, system, and storage medium based on virtual characters. Starting from the first-person perspective of the virtual character under test, it first acquires the game scene currently visible to the player through the visible range, and then obtains scene function data, such as interactive items, NPCs, and quest points. Subsequently, this function data is combined with the virtual character's own information, and a series of simulated operation paths are generated using a behavior planning algorithm. Each path represents a series of actions the player might perform from that perspective, with the expected result pre-set for each step. Finally, each path is executed step-by-step in the game, and the actual results are compared with the preset results to obtain the pass / fail information for each path. In this way, by automatically generating a complete operation sequence matching the player's perspective, it helps to trigger hidden vulnerabilities, thereby improving test coverage and defect discovery efficiency.

The invention discloses a chip support appearance defect detection method based on adaptive sequence modeling and matching. The method comprises the following steps: 1) image acquisition and preprocessing; 2) image correction and interception; 3) carrying out adaptive sequence modeling; 4) dynamic matching detection; and 5) result feedback. According to the method, the adaptive sequence modeling and the dynamic sequence detection are integrated to realize the adaptive, accurate and efficient appearance defect detection of the sliced chip bracket product, and the adaptive sequence modeling improves the adaptability of the method to different product step pitches (repetitive unit lengths) and the head and tail differences of the product slices and reduces the modeling difficulty and complexity; the dynamic sequence matching detection realizes accurate and efficient matching detection of the product sequence image, and improves the adaptability to the random slippage condition of the product movement.

The invention provides a sequential sequence fragment search method and system based on multilevel features, relates to the technical field of sequential signal processing, and solves the problems of instability and subjectivity when data analysts manually judge a current sequential sequence. The method comprises the following steps: firstly, slicing time sequence data in a time domain dimension to obtain a plurality of time sequence fragments, and then correspondingly extracting multi-level features including parameter statistical distribution features, differential statistical distribution features and expert-level features; and performing weighted summation on the multilevel features of the sequential sequence fragments to obtain corresponding comprehensive features, and comparing the comprehensive features of the sequential sequence fragments to be searched and matched with the comprehensive features of a plurality of sequential sequence fragments of historical sequential sequence data stored in a database to obtain the closest historical sequential sequence fragment. According to the method, the most similar sequence matching of the time sequence can be realized, and the judgment accuracy and the analysis efficiency of data analysts can be improved by assisting the data analysts.

The invention relates to the technical field of fault detection, in particular to a building drainage pipe network anomaly detection system which comprises a water pressure chain construction module, a sudden drop identification module, a flow resistance classification module, a structure mapping module and an attribution verification module. According to the method, the continuous change chain is constructed between the water pressure monitoring points of the drainage pipe network, and the spatial correlation analysis is realized according to the water pressure direction and amplitude change of the adjacent nodes, so that the abnormal region can be quickly identified by taking the chain type water pressure gradient fracture as a clue; in abnormal sudden drop identification, timing sequence matching of upstream springback and downstream delay is used as a verification condition, so that abnormal judgment has a dynamic response basis, flow resistance type division is formed through water pressure curve trend segmentation matching, and hierarchy and pipe section attribution positioning of abnormal positions is realized; a closed-loop detection mechanism from signal chain change identification to spatial path confirmation is realized on the whole, so that the drainage system abnormity diagnosis has continuity, traceability and improved positioning precision.

The invention discloses a tumor specific signal analysis device and equipment for uncertain pulmonary nodules and a storage medium, and relates to the technical field of electrical digital data processing.The device constructs a LungTCR database containing lung cancer tissue enrichment type and blood enrichment type CDR3 sequences through TCR beta chain sequencing and IMGT database comparison, and the LungTCR database is used for analyzing the lung cancer tissue enrichment type and blood enrichment type CDR3 sequences. A basis is provided for tumor specific signal recognition; a Needleman-Wunsch algorithm and an editing distance threshold value are adopted for screening, so that high-precision sequence matching is realized; through quantification of lung cancer tissue scores, blood scores and mutation specificity scores, a TCR feature group with biological significance is formed; and finally, the TCRnodseek plus model trained by clinical and image features is combined, a reliable malignant probability prediction value can be output, the model AUC can reach 0.90 or above, and the model is obviously superior to traditional imaging diagnosis and tumor markers.

The invention relates to the technical field of digital identity authentication, in particular to an online insurance policy verification method and system and a storage medium. The method comprises the following steps of: authenticating a user identity by adopting a living body detection and certificate OCR (Optical Character Recognition) technology, identifying tampering by using an image tampering detection model, and generating a structured request data packet through an improved OCR content extraction technology; retrieving benchmark insurance policy data in a distributed insurance policy database, and calling a multi-version data fingerprint sequence from a block chain; comparing the reference insurance policy data with the structured request data packet, and outputting a first verification result; matching the structured request data packet with the multi-version data fingerprint sequence, and outputting a second verification result; and generating a final verification conclusion based on the first and second verification results. According to the method, multiple technologies are fused to construct a whole-process verification system, compared with a single verification mode, the anti-fraud capability is improved through multi-dimensional cross verification, and related requirements of financial supervision on Internet insurance services are met.

The invention relates to the field of lifting intelligent control, and particularly discloses a lifting control method and system based on user habits, which transfer a lifting control trigger source from a single time dimension to a digital behavior of a user, and identify a workflow context with semantic depth by performing atomic classification and sequence matching on an application activity flow. Furthermore, a dynamically updated habit portrait is constructed, and the portrait introduces an enhancement mechanism for a semantic isolation defect: during decision making, not only direct historical preferences are extracted, but also prior knowledge of adjacent scenes is aggregated based on a context graph, and a Bayesian formula is utilized to perform weighted fusion on direct experience and reasoning prior. Therefore, when the real-time working state of the user can be captured, intelligent generalization reasoning is carried out on a new scene which is not seen by using experience of similar scenes, and non-inductive lifting control with personalized accuracy and cold start robustness is realized.

The invention discloses a dynamic quantitative evaluation method and device for comprehensive risks of network public opinions, and the method comprises the steps: constructing an index system of network public opinion risk symptoms, the index system comprising a public opinion symptom index set and a public opinion symptom index association graph; based on an actually occurring public opinion risk event sequence, matching a public opinion symptom index set, generating an incidence matrix according to the public opinion symptom index association graph, and quantifying an association risk value of each public opinion risk event through risk intensity; based on a risk time sequence attenuation model, performing time attenuation calculation on the associated risk value of each public opinion risk event to obtain a real-time risk value; on the basis of all real-time risk values, the comprehensive risk index of the network public opinions is calculated through an improved logistic model, factors in multiple aspects are considered, mathematical modeling is combined to simulate a real scene, and a wait index association diagram, a risk time sequence attenuation model and the improved logistic model are introduced in the calculation process, so that the evaluation result tends to the real situation more.

The invention discloses a grouting construction intelligent control system and method based on double-liquid slurry, and the method comprises the steps: obtaining multi-source state data formed in a grouting construction process, and obtaining a fluid state formed in a double-liquid conveying process; inputting the multi-source state data and the fluid state into a construction knowledge structure; identifying a field dependency relationship between the multi-source state data and the fluid state, and establishing a dynamic coupling relationship graph for reflecting construction process logic; and performing hierarchical deconstruction on the construction knowledge structure according to the dynamic coupling relation graph, extracting a step identifier corresponding to the current construction stage, and generating a control sequence matched with the step identifier. Through dynamic modeling and self-adaptive control, the whole-process intelligent management of the double-slurry grouting process is realized, and the construction precision, stability and real-time response capability are remarkably improved.

The invention discloses a low-voltage topology identification method, system and device based on characteristic current real-time sampling analysis and a medium, and relates to the technical field of data processing, the identification method comprises the following steps: collecting sampled current signals in real time through a master control intelligent terminal, and carrying out grouping detection; dynamically selecting three detection points on a current signal propagation path, calculating a distribution characteristic value based on a spatial position coordinate, and generating a topological matching correction coefficient K; according to the correction coefficient K, dynamically adjusting a fault-tolerant threshold value matched with the sequence, and if an adjusted matching result meets a condition, generating an identification record representing that a connection relationship exists between the current sending node and the sampling node; and recursively sorting the hierarchical relationship of all the generated identification records according to the number of identification times of the nodes from low to high until identification and redisk of all the nodes are completed, and generating and storing a final topological structure. According to the invention, the operation and maintenance efficiency and the intelligent level of the power grid are improved.

The invention provides a main and standby switching method and system for a water dispatching automation system, and relates to the field of water dispatching automation and data processing. The method aims at solving the problems that in an existing method, business event flow sequential logic is ignored, and instructions are prone to being disordered and lost due to switching. The method is applied to a framework comprising a main system, a standby system and a time source, and the main system and the standby system are synchronous in time. When executing the water dispatching control instruction, the main system generates a water dispatching event containing instruction content and a timestamp, and stores the water dispatching event in a shared event sequence cache region; the standby system periodically pulls an event, simulates execution after verification by a business rule engine in combination with an associated context, constructs an event node tree diagram with a weight, and prunes based on an actual result; and when the switching is triggered, comparing the actual result of the main system with the execution sequence of the standby system, matching an adaptive path, and avoiding error instruction marks. The method guarantees the time sequence consistency and logic correctness of the event flow, achieves the intelligent seamless switching of a main system and a standby system, and guarantees the continuous and stable operation of a water dispatching service.

This invention discloses a dynamic data security assessment system and protection method, belonging to the field of information security technology, and is used to solve the problem of dynamic collaborative protection of terminal device access control and behavioral risks. It generates fingerprints based on terminal device characteristics and verifies authorization. Authorized terminal devices input access feature slices into a time-series model. A trust score is generated based on the cosine similarity between the behavioral sequence and the predicted sequence. A Markov model is then constructed to dynamically select the authentication method. A risk index is calculated by combining network and geographic information and assigned to the real or virtual environment. Unauthorized terminal devices are assigned to a virtual environment after registration. Differential monitoring is implemented: a time-series database is established for virtual environments, and a suspicious score is generated through sequence matching; for real environments, a state deviation is calculated using a Hidden Markov Model and multi-dimensional features are fused to generate a risk score. Based on result-based access control, suspicious terminal devices have their permissions restricted, compliant terminal devices undergo authentication migration, and access is controlled according to the principle of least privilege and a time window mechanism.