25 results about "Computer file" patented technology

The invention provides an asynchronous file generation and downloading realization method and system, and relates to the technical field of computer file processing, and the method comprises the steps: receiving a user file downloading request, creating a task, and generating a unique identifier; dividing the task into a plurality of sub-task segments based on a file feature recognition rule and allocating resources; distributing the subtasks to a plurality of processing nodes to generate subfiles in parallel; merging the sub-files into a target downloading file and uploading the target downloading file to a server cluster; and returning the file in response to user query. The large file downloading efficiency is improved, the system stability is enhanced, and the user experience is optimized.

The invention discloses a computer file protection method, which relates to the technical field of computer information security, and comprises the following steps of: S1, classifying files and marking security levels based on content characteristics and sensitivity; s2, dividing system user permission levels and configuring a multi-factor authentication mechanism; s3, constructing a file access control matrix and setting a fine-grained operation authority rule; s4, deploying an access behavior monitoring module, and recording a file operation behavior log in real time; s5, performing dynamic risk analysis based on behavior modeling and an anomaly recognition algorithm; s6, performing hierarchical response according to the risk level, wherein the hierarchical response comprises measures such as warning, limiting, network disconnection and locking; and S7, encrypting and storing the log information, and providing an auditing interface for behavior traceability. According to the method, static permission control and a dynamic behavior recognition mechanism are fused, full-process intelligent protection of files from creation, access, transmission to storage is achieved, and the method has the advantages of being high in safety, timely in response, capable of achieving self-adaptive evolution of strategies and the like.

A cloud-based file integrity monitoring service identifies content changes to a computer file. An endpoint cybersecurity agent monitors its host client device for read / write and other operating system events associated with the computer file. When the endpoint cybersecurity agent detects each operating system event, the endpoint cybersecurity agent captures and reports, in real time or near real time, a snapshot of the file content representing the computer file. So, as the host client device changes the computer file with each operating system event, the endpoint cybersecurity agent uploads timestamped snapshots of the file content to a cloud-based file integrity monitoring service. The cloud-based file integrity monitoring service stores each snapshot of the file content, thus logging a change history for the computer file. The cloud-based file integrity monitoring service may thus retrieve and analyze different snapshots at different points in time, thus quickly identifying the content changes to the computer file.

For improving the efficiency of malware detection, a method is proposed that can handle computer files (1) of varying types and sizes and at the same time maintain a high detection performance by classifying a number of different types (A, B, C, D, E) of images (4), each calculated or derived from a particular computer file under test (1) (CFUT), using artificial intelligence methods such as machine learning, in particular deep learning, for example as provided by neuronal networks (24) or supervised deep learning algorithms. The different image types (A, B, C, D, E) are generated using different image conversion techniques and a number of approaches are presented for computing images (4) of uniform size Si that contain relevant information for classifying the CFUT (1).

The invention discloses an intelligent computer archive classifying and filing method. The method relates to the technical field of archive digital management, and comprises the following steps: step 1, acquiring an image of an archive to be archived, and preprocessing the image of the archive; 2, identifying the preprocessed archive image based on OCR image identification software to obtain an initial identification result of archive characters; 3, constructing a semantic analysis model, carrying out semantic analysis on the file character initial recognition result, and outputting a high-precision character recognition result, and 4, based on the high-precision character recognition result, searching a preset target identification character, and carrying out matching classification; step 5, generating hierarchical directory information based on a matching classification result; and step 6, completing archiving storage in combination with a matching classification result and directory information. According to the method, character context semantic association and global sequence logic can be effectively captured, file semantic accurate analysis is realized, and low-confidence character and terminology errors in OCR initial recognition are greatly corrected.

The invention discloses an intelligent computer file classification management system based on artificial intelligence, which comprises a data acquisition and processing module, a file management module, a file management module and a file management module, the multi-modal feature extraction module performs extraction and cross-modal fusion on multi-modal data based on a BERT pre-training model, a ViT-Base, a graph neural network and a gating attention mechanism, and the knowledge graph construction module is used for constructing and updating a knowledge graph based on file features and an external knowledge base. The adaptive classification module completes classification decision and identifies unknown categories based on global features and knowledge graph association information, and the dynamic optimization module is used for optimizing a classification model and a knowledge graph through user feedback and incremental learning; according to the system, the classification accuracy of complex files can be improved, rapid adaptation of new file types can be supported, meanwhile, continuous optimization of the classification model and the knowledge graph is achieved, and the manual rule maintenance cost can be reduced.

A method for protecting resources on a computer file system. Also provided, is a computer program product configured to adapt a computer to carry out the method comprising: a file system filter driver

This invention relates to the field of computer file system technology, and in particular to a file system kernel service and high-concurrency scheduling method based on a unified protocol. The method includes the following steps: Step 1: Starting a receiving thread and a file operation thread on the server side, the file operation thread including a lightweight thread and a heavyweight thread; Step 2: Listening to the network port through the receiving thread to receive JSON-formatted requests sent by clients, the requests containing timestamps and operation types; operation types include copy, move, create directory, delete, list, and restore; Step 3: Storing the received requests in a receiving queue; Step 4: Retrieving requests from the receiving queue and distributing them according to the operation type; Step 5: Executing the operation; This invention exposes file operation capabilities through independent processes and a unified JSON protocol. The six types of operation semantics, as well as the semantics of abort and recoverable deletion, are all uniformly defined at the protocol layer. The dual-type threads and request queue improve throughput and stability under multiple clients and large-scale tasks.

Visual representations represented in computer files can undergo various changes, in terms of specific visual details in a visual representation, without changing the semantics of what is represented. The present disclosure provides techniques and solutions for generating an identifier for a visual representation using one or more content-independent semantic metadata elements. Content-independent semantic properties are those that do not correspond to individual visual elements in a visual representation, or to properties of a visual representation that do not contribute to a description of an overall semantic provided by the visual representation. Disclosed techniques can be used to identify when a visual representation is generated or imported that has the same overall semantic, as indicated by the identifier, as another visual representation. The two visual representations can have the same or different image elements. Disclosed techniques also provide that visual representations that have a different overall semantic are assigned different identifiers.

This invention discloses an automatic computer protection system and method, relating to the field of computer file security protection. The technical solution includes: detecting user idle time; identifying sensitive tabs in the browser when the user is about to leave, and extracting the ORB feature point set of their content area as a content fingerprint; creating a Gaussian blur overlay window when the user has left, tracking the positional changes of the content area through feature point matching and affine transformation, and dynamically adjusting the position and size of the overlay window so that the overlay always follows the movement of the file content; and destroying the overlay window when the user returns, restoring the file to normal display. This invention, through content area tracking based on visual features and progressive blurring, solves the problem of sensitive file content being exposed and background tasks being interrupted when a user is briefly away, achieving fine-grained protection at the file and tab levels, and helping to improve the security of computer files in the office environment.

The application provides an asynchronous file generation download implementation method and system, relates to the technical field of computer file processing, and comprises the following steps: after receiving a user file download request, a task is created and a unique identifier is generated; based on file feature identification rules, the task is divided into multiple subtask segments and resources are allocated; the subtasks are allocated to multiple processing nodes to generate subfiles in parallel; the subfiles are merged into a target download file and uploaded to a server cluster; and the file is returned in response to a user query. The application improves the large file download efficiency, enhances the system stability, and optimizes the user experience.

A system and computer-implemented method for approving a dynamic mortgage application. In one aspect, the method may include determining a customer is approved for a mortgage and determining a real estate property is mortgage ready, including calculating an appraisal value for the real estate property based upon the information about the real property retrieved from a computer file or memory location / address (such as by using a machine learning or artificial intelligence algorithm). The method may still further include comparing the calculated amount the customer is approved for a mortgage loan with the calculated appraisal value of the real estate property; and approving the mortgage application of the customer for the real estate property when the calculated amount the customer is approved for the mortgage loan meets, or exceeds, the calculated appraisal value of the real estate property.

A method for a space profile interpreter framework is described. The method includes a data interpreter module receiving a first data file having a data section that includes data representing real-world entities for a layer of a digital geographic structure. The data interpreter module communicates with a computing system for managing a location hierarchy. The module extracts location information included in multiple entity records for the layer. Each entity record corresponds to a respective space profile feature for a real-world entity of the digital geographic structure. A mapping module of a computing system associates the data item of the extracted location information with entity information of the location hierarchy managed by the computing system.

A method of protecting access to files on a computer file system is disclosed. A kernel-mode file system filter driver controls access to stored policies. Some access policies will cause the file system filter driver to send a request to a user-mode policy configuration service. The user-mode policy configuration service includes features allowing safe autoconfiguration of policies for new applications, and safe reconfiguration of policies for updated applications.

A deterministic finite automata (DFA) is used by an extended Berkley packet filter (or “eBPF”) to monitor file system operations and non-file system operations. The DFA is stored as an eBPF map. Before a kernel of an operating system executes any file system operation, the kernel runs an eBPF program that queries the DFA for a filename associated with the system operation. The DFA represents safe / suspicious filenames associated with computer files. If the filename matches the DFA, then the kernel notifies a cybersecurity agent. The cybersecurity agent may then block or allow the file system operation, depending on whether the filename is safe or suspicious. The DFA stored in the extended BPF thus greatly improves computer functioning by very quickly and simply identifying safe / suspicious operations.

The application provides a file acquisition method and device, computer equipment and a storage medium, and the method comprises the following steps: acquiring the clipboard data of a first target object, wherein the clipboard data comprises the storage path information of a first file and a first operation type performed on the first file; after the clipboard data is written into the clipboard corresponding to a second target object, the storage path information of the first file is replaced by the storage path of a second file which is pre-constructed, wherein the second file is a file created on the second target object; when a preset operation is performed on the second file, response information corresponding to the preset operation is generated; the response information is fed back to the first target object side, so that the first target object transmits the operation result to the storage path of the second file according to the response information. The application can realize that the user can copy or cut any local file as operating a local computer file, and paste the file anywhere in the cloud desktop.

Data backups are performed in multiple blockchain environments. Digital pictures, movies, computer files, apps, and any other electronic data may be automatically backed-up, or duplicated, to multiple blockchain networks. First, an electronic data is written to a first blockchain network. A second, different, blockchain network is automatically selected based on many factors and / or parameters. Then, the electronic data is written to the second blockchain network. Still more duplicate copies of the electronic data may be redundantly written to third, fourth, and more blockchain networks. Any of the blockchain networks may send a confirmation that confirms the duplicate copy was written. One or more cryptographic proofs may be generated to prove the duplicate copies were stored to the multiple blockchain networks.

Embodiments described herein provide systems and methods that allow for the archiving of computer data and computer files by aggregating archival content on various types of Removable Digital Storage Media. The system that supports the archiving is a triplex data structuring system providing at least three separate data pools working in synchrony for the stability of the data. Various methods are described to write data, to read data, to virtualize the data, to store data chronologically, to aggregate small files, to screen for malware, and to create various modes of redundancy that allow for the reconstruction of the system even after catastrophic failures.

Method and systems for assisting a user on a computer-implemented user platform. The method includes receiving a user input from a user and determining an input category of the user input. In response to the input category being a first input category, the method includes accessing a first database hosting static computer files associated with document embeddings, determining a relatedness score for each static computer file and returning an indication of at least one of the static computer files based on the relatedness scores to the user. In response to the input category being a second input category, the method includes accessing a second database hosting executable dynamic computer files associated with service embeddings mapping a function thereof, determining a relatedness score for each dynamic computer file, executing at least one dynamic computer file and returning an indication of an output of the execution to the user.

A Wearable Medical System (WMS) that implements a wearable cardioverter defibrillator (WCD), includes a microphone and related improvements. The microphone can be on the same dongle as the cancel switch of the WCD. A user trigger module may permit the patient to perform a deliberate act and, in response, the system may start recording audio from the ambient sounds, including their own voice, and / or start recording the ECG. The deliberate act may even be a voice command by the patient that is parsed by a voice recognition module. The WMS may continuously record audio and then continuously discard it, and further stop the discarding if it detects a recording trigger. The WMS may create an exportable computer file that has audio-related data, which can have playable sound data or transcribed voice data.

METHOD AND SYSTEM FOR CORRELATING COMPUTER FILES, IN PARTICULAR FOR DETECTING MALICIOUS COMPUTER FILES. The invention relates to a method for correlating an analyzed file (102) with a database (104) of files, characterized in that it comprises a step (112) of training a machine learning model (106) configured to obtain a set of characteristic functions associated with a file, a step (114) of determining the basic functions of the analyzed file (102), a step (116) of vectorizing the analyzed file (102) to obtain a set of vectors, each associated with at least one basic function of the analyzed file (102), and a step (118) of processing the vectors of the set of vectors by the machine learning model to associate a characteristic function with each vector.a step (120) of comparing the set of characteristic functions associated with each vector with a database (108) of characteristic functions, a step (122) of correlation between the analyzed file and the files in the database. Figure for the abbreviation: Figure 1,

The present application belongs to the field of computer file system, and particularly relates to a method and system for restoring temporary data in unused space of a disk, wherein the method comprises the following steps: S1, acquiring all disk running data in a networking state of a user computer system; S2, locating a data area of the disk, extracting temporary data in unused space of the data area, and classifying the temporary data in the unused space according to preset file information features to generate a retention file feature table; and S3, reading the retention file feature table, and processing according to a preset restoration measure according to the completeness of the retention file feature table. The present application can solve the problems of high restoration difficulty and high restoration cost in the prior art when data is restored under the premise that the user's backup awareness is weak.

A method for securing one or more computer files includes obtaining at a computer device having a file and at a handset device data based on movement of at least one of the devices with the respect to the other device and generating an encryption key based on the obtained data at each of the devices wherein the key at each of the devices is substantially the same, and encrypting the file on the computer with the encryption key, discarding the computer encryption key and saving the handset encryption key. Later, the encryption key saved on the handset can be used to decrypt the encrypted file. Further, the method can be used to secure a plurality of files with the generated encryption key.

The embodiment of the application provides a kind of document management method, management system and storage medium, belong to computer file management technical field.The document management method includes: in response to operation instruction trigger signal, the state information of target document is collected;Based on operation instruction and the state information of the target document, the state correction rule of the target document is generated;Based on the state correction rule of the target document, the state information correction of the target document is carried out, and the new state information of the target document is obtained;Based on the new state information, the target document is archived.The application scheme realizes the differentiated management of the whole life cycle of document by guaranteeing the real-time update of document state, improves the targeted management of each document, effectively distinguishes management responsibility, and guarantees management efficiency and management accuracy.

The invention relates to a method for correlating an analysed file (102) and a database (104) of files, characterised in that the method comprises a step (112) of training a machine learning model (106) configured to obtain a set of characteristic functions associated with a file, a step (114) of determining basic functions of the analysed file (102), a step (116) of vectorising the analysed file (102), in order to obtain a set of vectors each associated with at least one basic function of the analysed file (102), a step (118) of processing the vectors of the set of vectors by the machine learning model in order to associate a characteristic function with each vector, a step (120) of comparing the set of characteristic functions associated with each vector with a database (108) of characteristic functions, and a step (122) of correlating the analysed file and the files of the database.