439 results about "Regular expression" patented technology

Artificially intelligent systems and methods for financial coaching provide personalized, fiduciary-compliant financial guidance through advanced machine learning architectures with measurable performance criteria. The systems implement privacy-preserving processing pipelines that detect personally identifiable information using multi-layered pattern recognition including regular expressions for formatted data sequences, named entity recognition with confidence thresholds above 0.85, and contextual analysis algorithms. A multi-step artificial intelligence processing workflow includes automated language detection, emotional tone classification with confidence scoring, financial profile transformation using predefined templates, context-aware question rephrasing, and semantic similarity matching employing vector embeddings with financial domain vocabulary weighting applying multiplier values between 1.3-2.0. Specialized training methodologies expand datasets through mathematical transformation functions utilizing statistical standard deviations with incremental variations between 0.5-2.0. Mood-based escalation logic automatically transfers users to human advisors when emotional indicators exceed confidence thresholds above 0.8. The systems maintain response times below 5 seconds while providing regulatory compliance through curated content sources and predefined fiduciary instruction parameters.

The invention discloses a financial sensitive data desensitization method and device, equipment and a storage medium, and relates to the technical field of data security, and the method comprises the steps: recognizing a sensitive data segment of to-be-desensitized financial data in an interface request, obtaining a sensitive data type and a target specific character position, and storing the sensitive data type and the target specific character position; determining to-be-encrypted data in the to-be-desensitized financial data by using a preset regular expression and based on the target specific character position; extracting a first preset number of bits of data from dynamic identification information corresponding to the to-be-desensitized financial data to obtain a first type of characters, and intercepting a second preset number of bits of data at the tail of the to-be-desensitized financial data to obtain a second type of characters; and combining and encoding the first type of characters and the second type of characters to obtain an initial character sequence, encrypting the to-be-encrypted data by using a target converted character sequence obtained by carrying out system conversion on the initial character sequence to obtain encrypted data, and desensitizing the to-be-desensitized financial data based on the encrypted data to obtain desensitized financial data. Therefore, the data desensitization efficiency can be improved.

The invention discloses a component identifier matching method and system based on NLP semantic segmentation and a multi-level word library, and relates to the field of constructional engineering informatization, and the method comprises the steps: building a standard main word library and a preset compensation word library, carrying out the semantic segmentation of an input component identifier, and obtaining a segmented lexical element sequence, calculating semantic similarity and morphological similarity between the segmented lexical element sequence and entries in a standard main word bank, and performing standard term mapping based on the semantic similarity and the morphological similarity to obtain a standard term mapping result; carrying out structured data conversion on the segmented lexical element sequence which does not complete the standard term mapping by utilizing a regular expression mode to obtain structured data, and carrying out AI extension library matching on the segmented lexical element sequence which does not complete the structured data conversion to obtain a synonym matching result; and combining the standard term mapping result, the structured data and the synonym matching result to obtain component identification description. By implementing the method, the matching accuracy of the component identifier names in the engineering project can be improved.

The invention discloses a phishing document de-obfuscation and feature extraction method and an application thereof in attack detection. The de-obfuscation comprises the steps of obtaining an obfuscation macro code of a phishing document, constructing a prompt engineering template by utilizing a pre-training language model, analyzing an obfuscation logic structure and generating a de-obfuscation rule and a reduction strategy; the method comprises the following steps: structuring a confused macro code into an abstract syntax tree through an analysis tool, matching a typical confusion mode based on a regular expression, and performing simulation and cell reference analysis in combination with a function to realize structure preliminary reduction, control flow semantic reduction and operation path construction; according to the unmixing rule and the abstract syntax tree, the confusion structure is converted into a readable macro statement, a macro code instruction sequence with confusion semantics removed is generated, and a semantic sequence obtained after unmixing is output. The feature extraction comprises word feature extraction, Token feature extraction, abstract syntax tree feature extraction and relation feature extraction. According to the method, the bottleneck that traditional phishing attack detection and confusion documents are difficult to recognize is broken through, and the detection accuracy of phishing document attacks is improved.

The invention relates to the technical field of policy matching, and discloses an intelligent matching system based on big data and a matching method thereof. The system comprises a data acquisition module, a condition analysis module and an intelligent matching module. The data acquisition module is used for acquiring policy text, enterprise qualification and historical case data and constructing a matching basic database; the condition analysis module is used for extracting policy dominant conditions through a regular expression, mining implicit conditions from failure cases by utilizing an association rule algorithm, and calculating condition weights by adopting a random forest algorithm; the intelligent matching module integrates dominant and implicit conditions to calculate a matching coefficient, dynamically divides risk levels and generates an early warning, the matching comprehensiveness and the early warning sensitivity are improved by mining the implicit conditions, dynamically adjusting the matching model and reinforcing a learning optimization mechanism, upgrading from text matching to risk prejudgment is achieved, and the method has the advantages of being high in practicability and easy to popularize. The enterprise declaration success rate can be improved, and the repeated declaration rate is reduced.

The invention discloses an interaction control method and system for an intelligent agent and a front-end and back-end system, and the method achieves the automatic control of the intelligent agent on the front-end and back-end system through the integration of a large language model. The method comprises the following steps: an intelligent agent performs natural language intention recognition through a large language model, automatically selects a proper tool, extracts parameters required by the tool, converts the intention into a target task, generates a structured control instruction, maintains a complete session history and supports multiple rounds of dialogue interaction; the back end receives a user request, calls an intelligent agent to generate a structured instruction, transmits the structured instruction to the front end, and dynamically adjusts a subsequent instruction according to the received front end feedback; and the front end receives the instruction transmitted by the rear end, automatically identifies an instruction format through a regular expression, performs corresponding operation after parameter verification and feeds back a result. According to the method, unified control of the agent on the front-end UI and the back-end business logic is realized, complex multi-round dialogue and multi-step operation are supported, and the method has a wide application prospect.

The invention relates to the technical field of data processing, in particular to an LLM-based multi-source heterogeneous data intelligent fusion and self-adaptive processing method, which comprises the following steps of: receiving multi-source heterogeneous data, matching character sequences of mailbox fields and identity card number fields in records one by one by adopting a preset regular expression model, according to a preset key value pair mapping dictionary, items are uniformly converted, data records which cannot pass format verification, type conversion and value domain mapping are marked as doubt, and data records which cannot be processed or are marked as suspicious are separated. According to the method, a hierarchical processing flow is constructed, and deterministic format verification, type conversion and value domain mapping are arranged at the front end of a processing link, so that most simple data quality problems can be quickly processed with low calculation overhead. Then, numeric statistics and character string comparison are used to carry out fuzzy correction on the data, and spelling errors and numeric abnormities which cannot be covered by rules are further solved.

The invention relates to the field of large model security testing, and particularly provides a large model output content security testing method and device, and the method comprises the following steps: S1, preparing and managing a test set, a sensitive word library and a regular expression which are required by testing; s2, reading a test set, and obtaining a large model output result according to the test set and the large model interface information; s3, judging whether the output content of the large model is safe or not according to the sensitive lexicon and the regular expression; s4, extracting semantic risk features according to the output content of the large model by using the large model and the oriented Prompt, and automatically storing the semantic risk features after confidence verification; and S5, storing the information result of each request in a file. Compared with the prior art, the test time can be shortened, and the evaluation efficiency can be improved; and the security of the output content of the large model can be effectively evaluated by using a method for dynamically constructing the sensitive word bank by using the output result of the large model.

The invention provides a non-deep traffic analysis streaming matching search analysis method, which comprises the following steps of: constructing a deep data packet detection architecture on the basis of a data platform development kit (DPDK); aiming at the non-encrypted traffic, establishing a multi-mode recognition mechanism combining a regular expression and a feature bit stream mode; aiming at the encrypted traffic, constructing an encrypted traffic feature library according to the statistical features, the protocol features and the behavior features; real-time risk detection of network traffic is realized by adopting a streaming matching search technology; and constructing an intelligent decision and response mechanism, and integrating flow analysis and identification results. According to the non-deep traffic analysis streaming matching search analysis method provided by the invention, real-time analysis, risk identification and supervision of network non-encrypted traffic and encrypted traffic are realized by taking a data platform development kit (DPDK) as a basis and combining a high-performance streaming regular expression engine and a finite-state machine principle; the method can be widely applied to scenes of network communication supervision, data security protection, malicious traffic monitoring and the like.

The invention discloses a rationality analysis method for acquisition and bidding evaluation information of power equipment, which comprises the following steps: constructing a regular expression to perform paragraph matching on preprocessed bidding document and bidding document texts, and extracting specific parameter contents; obtaining an absolute error and a relative error based on each bidding value and each bidding value, and comparing the absolute error and the relative error with a preset threshold to obtain a numerical deviation degree grade of the bidding file relative to the bidding file; the method comprises the following steps: splitting a bid invitation file and a bidding file into character sequences, creating a two-dimensional table, analyzing to obtain an editing distance value of each text, obtaining a comprehensive matching degree of the text through accurate matching and fuzzy matching based on a preset synonym library, and further obtaining a text deviation degree grade; constructing a deviation degree comprehensive evaluation rule matrix based on the numerical deviation degree grade and the text deviation degree grade of the bidding file relative to the bidding file, and obtaining a corresponding comprehensive evaluation result; according to the invention, the efficiency and accuracy of collection and bidding evaluation of the power equipment are improved, and personal errors and compliance risks are reduced.

The invention relates to a railway official document keyword extraction method and device and electronic equipment, and the method comprises the steps: based on a pre-constructed railway official document format rule base, extracting a key field of a fixed position from an input text through regular expression matching and position locking; a Jieba word segmentation device is used for loading a railway-specific term library for word segmentation, and a multi-word combination entity boundary is dynamically corrected through a dependency relationship rule; executing a TF-IDF algorithm on the text after word segmentation to generate an initial word weight, adjusting the weight according to the position area of the word in the official document and a preset coefficient, and performing position weighting; and combining the words of which the weights are greater than a set threshold value with the extracted key fields, and outputting a final keyword set after verification of a term library. According to the method, missing detection caused by low frequency of a traditional algorithm is avoided, splitting errors of a general word segmentation device are eliminated, the term recognition error rate is reduced, the core word sorting priority is improved, and the semantic weight of keywords is strengthened; the new term storage time is shortened, and the updating cost problem is solved.

The invention discloses a picture type PDF document analysis method based on a convolutional neural network, a multi-modal model and a regular expression, and belongs to the technical field of artificial intelligence and text processing. The method comprises the following steps: detecting types of layout elements of a preprocessed PDF document to obtain bounding box coordinates of each layout element; performing content identification on each layout element according to the type of the layout element; using a regular rule engine and a large language model to perform structured information extraction on the identification content, and extracting to obtain a plurality of predefined first business fields corresponding to each layout element; the character recognition result and the table recognition result are combined, and the combined result serves as content needing to be extracted; and taking a proofreading result as an analysis result of the scanned PDF document. According to the method, high-precision structured extraction of paragraphs, tables, formulas and other contents in the PDF document is realized, and the method has good universality, expandability and automation capability.

The invention relates to the field of high-performance computing cluster resource scheduling management, and discloses a Slurm scheduling specification integration method and system, and the method comprises the following steps: 1, analyzing a heterogeneous job description file, and extracting a resource demand parameter and a dependency relationship through a regular expression rule base; 2, based on the extracted original parameters, converting the original parameters into SLURM standard parameters through a preset mapping rule; step 3, according to the converted standard parameters; 4, calling a Slurm interface command to submit a script; and step 5, monitoring the execution state of the submitted job, and triggering a re-submission process for the abnormal job with the resource overrun or dependency missing. Through a multi-level analysis architecture and a regular expression rule base, job description files in different formats are effectively compatible, the problem that analysis of a non-standardized input format by a traditional method fails is solved, unified processing of cross-platform job definition is achieved, and the manual adaptation cost is remarkably reduced.

Systems and methods for generating an enhanced error message are provided. An example method includes: receiving one or more raw error messages. The one or more raw error messages include one or more stack traces. The method further includes matching at least one raw error message of the one or more raw error messages to one or more error rules from a plurality of error rules. The one or more error rules include regular expression patterns. The method further includes parsing the at least one raw error message, based on the one or more matched error rules from the plurality of error rules; and generating one or more enhanced error messages, based on the at least one parsed raw error messages. The one or more enhanced error messages include one or more natural language sentences. The method further includes embedding the one or more enhanced error messages into a website.

The invention discloses an automatic data cleaning and anomaly recognition method for financial auditing, and relates to the technical field of financial auditing. Extracting fields from the multi-source heterogeneous data by using a regular expression, and unifying the format through semantic mapping; repairing numeric missing data by using LSTM, and checking logic errors by using a rule engine; identifying abnormal transactions based on an isolated forest algorithm in combination with business rules; constructing a risk assessment matrix to divide risk levels; dynamic knowledge graph analysis implicit association can be constructed, an incremental learning optimization model is utilized, and an auditing evidence chain and block chain evidence storage are recorded. According to the invention, automatic processing of financial audit data is realized, the data recovery success rate is improved, and the anomaly identification accuracy is improved; hidden risks are mined through the knowledge graph, audit traceability is guaranteed through block chain evidence storage, manual annotation cost is reduced by 40%, and audit efficiency and reliability are improved.

The invention discloses an integrated circuit design Verilog code generation method and device based on a large language model, equipment and a medium, and relates to the technical field of computers, and the method comprises the steps that semantic analysis is conducted on an input language of an integrated circuit user side through the large language model, and a target constraint set is determined based on an obtained performance index set and through a regular expression; a candidate architecture scheme is generated by utilizing thinking chain technology reasoning, the candidate architecture scheme is predicted by utilizing an XGBoost regression model, and a target architecture scheme is determined based on an index prediction result and the candidate architecture scheme by utilizing a non-dominated sorting genetic algorithm; and determining an initial Verilog code based on the target architecture scheme and a preset code template library, and performing code style conversion on the initial Verilog code based on a code style feature corresponding to the integrated circuit user side to obtain a target Verilog code. And the efficiency and availability of integrated circuit design are improved.

The invention discloses a multi-modal fusion short message compliance and security dual auditing method and system, and the method comprises the steps: encrypting account information through employing an irreversible algorithm based on SHA256 and a random salt value, and decomposing the content of a short message into a text stream, a link stream and a symbol stream through employing a regular expression; traversing each character in the short message content by adopting a prefix mode based on a Trie tree in combination with an AC automaton algorithm to detect sensitive words; performing symbol semantic classification mapping and analysis on the special symbol feature data extracted from the symbol stream; carrying out sending behavior analysis on the text feature data extracted from the text stream; performing special detection on link feature data extracted from the link stream; based on the factors corresponding to the sensitive words, the semantics, the behaviors and the links and the weights of the factors, a multi-modal feature fusion decision risk assessment algorithm is adopted to output a risk score value and a risk decision rule of the risk score value so as to execute short message interception operation or short message release operation. According to the invention, full-dimension perception and dynamic defense of risks can be realized.

The invention discloses a permission matching method and device, and relates to the technical field of computers. The method comprises the following steps: acquiring a to-be-matched path; performing permission rule matching on the to-be-matched path based on a pre-constructed permission rule tree; when the permission rule in the permission rule tree is matched, determining a corresponding rule control permission based on the permission rule, and obtaining a permission matching result of the to-be-matched path; and when the permission rule in the permission rule tree is not matched, determining a preset default control permission as a permission matching result of the to-be-matched path. According to the method, the accurate child nodes, the single-wildcard child nodes and the multi-wildcard child nodes are integrated through the permission rule tree of the single tree structure, common permission matching scenes such as accurate matching, single-segment wildcard matching and cross-multi-segment wildcard matching can be covered without introducing a regular expression, the integrity of the expression ability is guaranteed, the implementation complexity is reduced, and the implementation efficiency is improved. And the system stability is improved. And meanwhile, the problem of matching logic confusion caused by traditional multi-rule scattered storage is avoided.

The invention relates to a project review-oriented large language model optimization training method and system, and the method comprises the steps: collecting multi-source heterogeneous data related to project review through a distributed crawler, converting the multi-source heterogeneous data into a model recognizable format through cleaning, desensitization, labeling and structural processing, and carrying out the recognition of the model. Extracting a text core paragraph through a regular expression, and desensitizing to obtain text data; based on the text data, extracting change points of the text data as policy change contents by comparing expressions of new and old policies; obtaining a historical project review report and extracting policy change content, project parameters and review results to form a training sample set; constructing a BERT model which takes the policy change content and the project parameters as input and takes the review result as output, and performing optimization training based on the training sample set; and utilizing the BERT model after optimization training to predict a project review result.

The invention provides a virtual equipment and variable data processing method for power monitoring, which realizes intelligent definition, calculation, alarm and visual data binding technology of virtual equipment and variables in a power monitoring scene by integrating MQTT, a memory database, a time sequence database and a relational database and combining a regular expression analyzer collaborative analysis mechanism. The system supports various data such as current real-time values, equipment attributes, accumulated value differences and historical data to form an expression, the real-time data is stored in a Redis database and the historical data is stored in a TD engine database by adopting an atomic storage strategy taking station + deviceid + measure as key values, and efficient query and atomic storage combination based on the Redis and the TD engine are realized through a unified API interface, so that the data display speed is greatly increased, and the data display efficiency is improved. The innovatively designed zero-code binding mechanism is based on a front-end data driving framework, and automatic binding of real-time acquisition variables, virtual variables and power monitoring display components can be completed without additionally developing an API (Application Program Interface).

The invention relates to a PID (Proportion Integration Differentiation) drawing element intelligent identification and topology reconstruction method based on visual detection, which comprises the following steps of: cooperatively extracting multi-modal information, detecting components based on improved YOLOv11, identifying all text labels in a graph by adopting PaddleOCR, and carrying out pipeline identification algorithm and merging filtering method based on probability Hough transform of pixel points. Identifying and defining the T-shaped connection point as a special topological node to obtain positioning information of components and characters in a PID drawing, associating the components with the characters by using a regular expression and an Euclidean distance, and converting image elements into a topological graph model with a semantic relationship; according to the method, the end-to-end automation process of detection-association-reconstruction is achieved, finally, display is conducted in a graphical interface mode, a data basis is provided for subsequent application such as drawing analysis, system simulation and equipment management, end-to-end automatic conversion is achieved, and efficiency is greatly improved.

A device may receive a plurality of documents and a plurality of questions for the plurality of documents, and may determine a plurality of ground truth answers corresponding to the plurality of questions. The device may normalize the plurality of questions to generate a normalized plurality of questions, and may select a set of most frequent questions from the normalized plurality of questions. The device may utilize regular expressions and natural language processing to generate, from the plurality of ground truth answers, a set of answers to the set of most frequent questions, and may dynamically select prompts for LLMs based on the set of most frequent questions and based on context provided to the LLMs. The device may optimize, based on the set of most frequent questions, the set of answers, the prompts, and parameters of configurations for the LLMs, accuracies of the LLMs to generate optimized LLMs.

The invention relates to the technical field of information security, and provides a log auditing unknown type log classification configuration method which comprises the following steps: step 1, inputting an API token and a basic link of an AI service through an AI configuration page, and storing data into a database; 2, inputting an original log sample to a log classification management page, and triggering an AI interaction module to generate a regular expression of a naming capture group; 3, calling an AI service through an HTTP request, converting an original log into a regular expression with a named capture group according to an instruction, and analyzing a return result; and 4, associating the generated regular expression with the custom log type, and storing the regular expression and the custom log type in a database. By integrating the AI model, a user can automatically generate a high-precision naming capture group regular expression without mastering regular grammar, the technical threshold is reduced, in addition, real-time processing of unknown log types is supported, the classification accuracy is improved to 95% or above, and the response time is smaller than or equal to 500 ms.

The invention relates to the technical field of artificial intelligence dialogue systems, and particularly discloses an artificial intelligence dialogue generation method based on natural language processing. According to the method, response certainty or diversity is adaptively adjusted according to a dialogue scene through a dynamic temperature sampling strategy, and historical dialogue key features are screened in combination with a gating attention mechanism to realize accurate semantic fusion; word embedding and primary coding are migrated to terminal equipment to be executed by adopting an edge-cloud collaborative architecture, and are transmitted to a cloud end through feature compression and encryption to complete deep decoding; establishing a dual-channel sensitive word detection mechanism of input regular matching and named entity recognition, and blocking privacy leakage through low-temperature sampling and risk word filtering in an output stage; and generating a four-dimensional metadata label driving decision containing the dialogue behavior type, the emotion polarity, the confidence coefficient and the interpretable vector. The method improves the generation quality in the algorithm layer, optimizes the deployment efficiency in the system layer, enhances the security and interpretability in the application layer, and is suitable for intelligent customer service, virtual assistant and other scenes.

The invention relates to a query statement display method and device, computer equipment, a readable storage medium and a program product. The method comprises the steps that in the process that a user inputs an initial query statement, a current character input by the user is scanned in real time based on a lexical analyzer in a regular matching mode; switching a dynamic lexical analysis mode of a lexical analyzer based on the character type of the current character, and analyzing the current character based on the lexical analyzer after mode switching; based on the analysis result of the current character, generating a structured lexical unit Token stream of the initial query statement, and based on a current Token corresponding to the current character in the structured Token stream, obtaining at least one recommendation value of the current character; and generating a target query statement based on a selection result of the recommended value by the user, and displaying the target query statement in a display interface of the user. According to the method provided by the invention, the actual input requirement of the user can be met.

The invention discloses a file transmission method and system for sensitive information identification and automatic blocking. The method comprises the steps that a network data packet in the file transmission process is captured, file content is analyzed, and related metadata is extracted; performing multi-level sensitive information detection on the extracted related metadata by fusing keyword matching, regular expression matching and semantic analysis methods; based on a multi-level sensitive information detection result, combining sensitive information severity, weight, file importance and information density to construct a weighted risk assessment model, calculating a risk value and dividing risk levels; when the risk level is judged to be high risk, file transmission connection is automatically interrupted, local cache data is cleared, and a complete audit log is recorded. According to the sensitive information identification method and device, through combination of various identification technologies such as keyword matching, regular expression matching and semantic analysis, the accuracy of sensitive information identification is greatly improved, sensitive information in various forms can be effectively identified, and the situations of misinformation and missing report are reduced.

The invention relates to the technical field of intelligent education systems, in particular to a subjective question automatic correction method based on multi-technology fusion, which comprises the following steps of: firstly, identifying whether a question is a strong proposition or not through a regular expression, and then performing knowledge point extraction, off-question judgment and double similarity evaluation on the strong proposition question; plagiarism detection, cosine similarity calculation and user-defined rounding are carried out on all the questions, and finally personalized comments are generated and correction results are output. According to the method, through double similarity evaluation, semantic relevance between answers and standard answers as well as questions is comprehensively considered, the misjudgment rate is remarkably reduced, meanwhile, through strong proposition recognition, knowledge point extraction and double similarity evaluation, the pertinence and accuracy of correction are remarkably improved, whether the answers of students meet the requirements of the questions or not can be deeply analyzed, and the correctness of the questions is improved. Misjudgment caused by insufficient semantic understanding in the prior art is avoided, and the method is particularly suitable for accurate scoring of strong proposition questions in subjective questions.

The invention relates to a text review method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: receiving an examination category and a to-be-examined text input by a user terminal; calling a corresponding prompt word according to the review category, inputting the to-be-reviewed text into the large language model, and outputting each review point and a confidence coefficient corresponding to each review point; loading a corresponding regular expression library according to the review category, performing rule matching on the to-be-reviewed text, and outputting hit review points and matching positions corresponding to the review points; performing deduplication merging on the review points to obtain target review points; and sending the target review point and the confidence coefficient and / or the matching position corresponding to the target review point to the user terminal. Therefore, the semantic comprehension ability of the large language model and the rule matching ability of the regular expression library can be combined, the examination texts of different examination categories can be comprehensively and accurately examined without depending on a large amount of standard data, the adaptation range is wide, and the flexibility is high.

The invention relates to the technical field of data processing, and discloses a special checking method and system for key natural resource assets. The method comprises the following steps: performing three-dimensional identification on mineral data through a resource classification matrix to generate a key resource list; recognizing coordinates in different formats by using a regular expression to form a standardized coordinate set; carrying out coordinate batch conversion by adopting a convolutional neural network; performing neighborhood interpolation correction based on the coordinate offset; and carrying out coordinate precision verification and anomaly repair, and outputting a checking data set containing quality scores. The technical problem that an existing natural resource asset checking method lacks key resource intelligent identification, specific format coordinate automatic conversion and coordinate quality intelligent control is solved.

The present invention relates to the technical field of data security, and in particular to an adaptive masking method and system, and a device and a medium. The method comprises: firstly, acquiring a keyword of a current file to be masked of a sender user; then, on the basis of the keyword, performing addition, deletion and modification on a current sensitive word library to obtain a new sensitive word library; and finally, generating a regular expression on the basis of the new sensitive word library, determining the positions of sensitive words on the basis of the regular expression, so as to obtain the sensitive words, and performing masking to obtain a masked file. Therefore, masking of a plurality of types of data is realized, and data types before and after masking remain unchanged, thereby ensuring the readability of a masked file while guaranteeing the security of masked data, and further increasing the masking speed; on the basis of different roles of receiver and sender users, the masking intensity is adaptively selected, thereby preventing important information from being leaked to untrusted persons, and overcoming the defect of an existing masking algorithm failing to resist collusion attacks and brute-force enumeration attacks; and multiple threads are used to concurrently process sensitive word retrieval and sensitive-word masking operations, thereby greatly increasing the masking speed.