18 results about "Computer virus" patented technology

Source code for a type of malware is received. For example, the source code may be source code from a type of computer virus. An Artificial Intelligence (AI) algorithm is identified. For example, the AI algorithm may be ChatGPT. The source code of the type of malware is run through the AI algorithm to produce mutated source code for the type of malware. A prediction algorithm is used to predict a signature of the mutated source code for the type of malware. For example, the prediction algorithm is trained using existing source code of different types of malware to generate a prediction model. The signature of the mutated source code for the type of malware is then compared to a signature of a potentially new type of malware to determine if the signatures are similar.

The present invention relates to a computer virus interception method. The method includes: executing the following steps by a processor unit: providing for a user to configure a default software status list by operating a default status configuration interface, wherein the default software status list includes a plurality of macro application software; providing for the user to configure a software whitelist by operating a software whitelist configuration interface; providing for the user to configure a hardware whitelist by operating a hardware whitelist configuration interface; and performing an identity re-authentication process to re-authenticate an identity information of the user when one of a default status change operation, a software whitelist change operation, a hardware whitelist change operation, and a software whitelist anomaly is detected.

The present invention belongs to the field of data mining technology and relates to a method for discovering the influence of key elements based on native-derivative topic transfer learning, including obtaining information including native topics and derived topics and related user information from an API interface provided by a social platform; constructing the early propagation network topology and propagation timing of derived topics, including using a joint distribution adaptive method to perform cross-domain feature adaptation on the content space of native topics and derived topics, and considering the sparsity of early data of derived topics, using an adversarial transfer learning method to compensate for the network structure; constructing a message-path-user ternary association graph of derived topics and performing cyclic iterative scoring to rank the influence of key elements of derived topics; the present invention can timely and accurately mine key elements in the early stage of the outbreak of derived topics, and the present invention can also be widely used in the precise placement of product advertisements, the discovery of important pathogenic genes, the prediction of popular research results, and the prevention of computer virus propagation.

The present invention discloses a method for countering encrypted ransom attacks, a solid-state drive, an electronic device, and a storage medium, which relate to the technical fields of data storage and data security, and include: adding a special flash translation layer for managing the mapping relationship between logical addresses and physical addresses to be recycled in the SSD, and continuing to use a conventional flash translation layer for managing the mapping relationship between logical addresses and physical addresses; equipping the SSD with a real-time clock chip to generate an RTC timestamp of the physical address, and responding to operation commands from the host based on the special flash translation layer, the conventional flash translation layer, and the real-time clock; providing a set of countermeasures and implementation technical solutions on the SSD hardware to support the production of highly secure SSD devices, which can identify and defend against all encrypted ransom attacks in advance; at the same time, it can also prevent other computer viruses from infecting and prevent internal privileged users from illegally tampering with programs, approaching the ultimate protection of the security of the data and executable programs stored in the SSD.

In an image forming apparatus, appropriate virus infection countermeasure processing is executed using a new virus scanning engine or the like, and a likelihood that the image forming apparatus may be infected with a computer virus is reduced.An information processing apparatus includes a print data acquirer that acquires print data, a virus detector that executes predetermined infection countermeasure processing on the print data and detects a computer virus, a virus scanning information generator that generates virus scanning information for specifying a setting item related to the infection countermeasure processing executed and adds the virus scanning information to print data in which a computer virus has not been detected by the virus detector, a print information generator that generates print information including print data requested from an image forming apparatus connected via a network among a plurality of pieces of the print data acquired, and a print information transmitter that transmits the generated print information to the image forming apparatus.

Embodiments of the present invention disclose a computer virus detection method, device, electronic device, and storage medium, relating to the field of computer security technology and capable of improving the speed of computer virus detection. The method comprises: opening a first file in response to a virus detection instruction; executing a first process of reading the first file and performing a first task for a second file; after completing the first task, determining whether the first process has ended; if the first process has ended, executing a second process of sending the first file to an antivirus engine and performing a second task for a third file; after completing the second task, determining whether the antivirus engine has completed virus detection; and if the antivirus engine has completed virus detection, closing the first file. Embodiments of the present invention are applicable to scenarios where computer viruses are detected.

The invention discloses a computer virus intelligent defense method and system based on data mining, and belongs to the technical field of network security, and the defense method comprises the following specific steps: I, collecting various behavior data in a computer system, extracting corresponding behavior characteristics, carrying out entropy modeling according to each behavior characteristic, and analyzing entropy fluctuation in real time; iI, constructing a heterogeneous threat relation graph according to an analysis result, and reasoning a threat propagation path based on the heterogeneous threat relation graph; according to the method, the whole-process defense capability can be improved, normal behaviors and potential threats can be effectively distinguished, false alarm and missing alarm are reduced, the capability of coping with unknown viruses, variant viruses and zero-day attacks is greatly improved, the viruses are prevented from reversely bypassing defense, a complex threat propagation chain can be accurately recognized, the active trapping and behavior reduction capability is improved, and the method is suitable for popularization and application. The attack chain tracking and threat tracing capability is improved, and the system robustness is improved.

The present application belongs to the field of computer information security technology, and discloses a computer virus detection method and computer equipment. In addition to matching the target process to be detected with the virus signature code, the scheme also matches the target process to be detected with the virus behavior characteristics, thereby realizing risk assessment of the dynamic real-time behavior of the target process, and making the computer virus detection result more reliable. In addition, a feature frequent item set of the process behavior characteristics is constructed, and feature association rules are generated for the feature frequent item set. Feature association rules with a confidence level above a preset threshold are determined as strong association rules. When the process behavior executed in the target process matches the prerequisite in the strong association rule, the security level of the subsequent behavior of the target process is further predicted, thereby realizing early warning of possible risks before dangerous behavior occurs, facilitating further disposal in advance, and improving the security of the computer system.

The application provides a computer virus retrieval method and device, computer equipment and a storage medium, relates to the technical field of computer security, and is used for improving the retrieval efficiency of computer viruses. The method mainly comprises the following steps: establishing a retrieval intermediate layer, and judging whether the virus information of the to-be-detected file is contained in the threat intelligence library based on the retrieval intermediate layer.

This invention belongs to the field of virus detection technology and discloses a virus detection method based on an improved clonal selection algorithm. The invention enhances population diversity by introducing a Halton sequence for population initialization, overcoming the uneven distribution problem caused by traditional random initialization methods. The evenly distributed population facilitates a more comprehensive exploration of the solution space, thereby enhancing population diversity. It also improves convergence accuracy and reduces the risk of local optimality: By balancing fitness and distance, the invention avoids premature aggregation of antibody populations in local optimal areas, effectively increasing population diversity and driving the search process toward the global optimal solution, thereby reducing the risk of falling into local optimality.

The invention relates to the technical field of computers, and discloses a computer virus protection method and system, and the method comprises the following steps: 1, collecting static feature information and dynamic behavior data of intelligent terminal equipment in a network, constructing an equipment portrait of the intelligent terminal equipment according to the static feature information, converging the device portrait and the dynamic behavior data into a shared data pool; and 2, extracting historical dynamic behavior data from the shared data pool, and establishing a normal behavior baseline model for the intelligent terminal equipment. According to the technical scheme of constructing the collaborative protection system covering the intelligent terminal equipment of the whole network, the data of all the intelligent terminal equipment in the network are collected and converged into the shared data pool for unified analysis and linkage response, so that the protection range is expanded from single equipment to a heterogeneous equipment network; the technical effect of integrated security coverage of all networking devices is achieved.

The present invention discloses a data attack adaptive system applied to a power network, including a power grid model construction subsystem and an immune configuration subsystem; the power grid model construction subsystem is used to construct a power grid immune neural model, and the power grid model construction subsystem includes an architecture management module, an associated feature management module, and an immune ability management module, simulating the training and tolerance process of immune cells in the human body, researching the generation and tolerance training methods of power system network attack detectors; researching the life cycle evolution strategy of detectors, forming an adaptive immune feedback process, and then adapting to the evolution and progression of network attacks in the real power system network environment, computer viruses, researching the real-time and quantitative calculation method of power system network dynamic risks; thereby achieving the effect of targeted identification and elimination of all computer viruses or data attacks.

The application provides a kind of computer virus library distributed storage method based on blockchain and its related device, it is related to distributed storage technical field, including any one storage node obtains the virus file reported by internet antivirus software, the virus file is stored in its disk array, and generates the summary information of the operation information and virus file of warehousing, operation information and the summary information of virus file are written into blockchain to generate new block;Any one storage node initiates a deletion request, and generates the summary information of the operation information and virus file to be deleted, after operation information and the summary information of virus file to be deleted are written into blockchain to generate new block, in the disk array of the storage node, virus file to be deleted is deleted, the present application is used to solve the technical problems that the warehousing management function of existing virus library is weak, the degree of automation is not high, and paralysis, data tampering and data loss exist.

An image forming apparatus includes a data inputter that receives job data pertaining to a print job; a job controller that stores job data in the memory as partial data to sequentially print received portions of the job data when the virus check is disabled or unnecessary and that stores the job data as a single file when the virus check is enabled; a data analyzer that analyzes the job data to generate data for image formation; and a virus checker that performs virus check on the job data stored as the single file, wherein the job controller causes the printer to perform printing based on the job data when the virus checker determines that a computer virus is not embedded in the job data.

The present invention relates to a computer virus interception method. The method includes: executing the following steps by a processor unit: providing for a user to configure a default software status list by operating a default status configuration interface, wherein the default software status list includes a plurality of macro application software; providing for the user to configure a software whitelist by operating a software whitelist configuration interface; providing for the user to configure a hardware whitelist by operating a hardware whitelist configuration interface; and performing an identity re-authentication process to re-authenticate an identity information of the user when one of a default status change operation, a software whitelist change operation, a hardware whitelist change operation, and a software whitelist anomaly is detected.

The embodiment of the present invention discloses a computer virus scanning method and device, which relates to the field of communication technology. The method includes: obtaining a preset collaborative scanning strategy; the collaborative scanning strategy includes a non-collaborative scanning directory and a collaborative scanning directory, the non-collaborative scanning directory is used to represent non-shared files in this terminal, and the collaborative scanning directory is used to represent shared files in this terminal; performing virus scanning on non-shared files to obtain a first scanning result; sharing the collaborative scanning directory to a preset collaborative terminal so that the collaborative terminal performs virus scanning on shared files to obtain a second scanning result; receiving the second scanning result sent by the collaborative terminal; generating a final scanning result based on the first scanning result and the second scanning result. A computer virus scanning method provided by an embodiment of the present invention realizes multi-terminal collaborative scanning, reduces the scanning pressure of a single terminal, and shortens the full disk scanning time of a single terminal.

The invention relates to the technical field of computer hardware devices, and discloses a computer virus prevention and control hardware device which comprises an installation mechanism and a control mechanism. The ventilation opening is formed in the top of the front face of the installation shell, the dust cover is fixedly installed on the inner side of the ventilation opening, the heat dissipation openings are formed in the two sides of the installation shell, the heat dissipation net covers are fixedly installed on the inner sides of the heat dissipation openings, and the lifting assemblies are arranged on one sides of the heat dissipation openings. According to the computer hardware device for preventing and treating the viruses, through an integrated mounting mechanism which comprises a ventilation opening, a dust cover, a heat dissipation opening and a heat dissipation net cover, the heat dissipation and dust prevention capacity of equipment is effectively improved, and the heat dissipation efficiency is further improved through a lifting assembly and a sliding groove, a sliding block and a heat dissipation part in the lifting assembly; flexible height adjustment and stable supporting are achieved through a power assembly and a bearing assembly in the adjusting mechanism, the stability and use convenience of the device are integrally improved, and the computer virus prevention and control hardware device is more efficient and durable.

The present invention discloses an automatic detection and calibration system for a display, comprising: a display screen of the display, a display screen detection and sensing module, a USB conversion module, a verification control module, a main control single-chip microcomputer of the display, a video processing module, and a data storage module; the display screen is connected to the display screen detection and sensing module; the present invention enables the display to perform self-check and self-verification regularly, reduces manual labor, securely stores the verified data, and avoids being attacked by computer viruses.