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Malicious software detection method and device

A technology of malware and detection methods, applied in neural learning methods, computer security devices, computer parts, etc., can solve problems such as terminal hazards and security risks, and achieve the effect of improving user experience

Pending Publication Date: 2021-01-01
HARBIN INST OF TECH SHENZHEN GRADUATE SCHOOL
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  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

Installing software in the terminal brings convenience to users, but also brings some security risks, because some malicious software may cause harm to the terminal

Method used

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  • Malicious software detection method and device
  • Malicious software detection method and device
  • Malicious software detection method and device

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Embodiment Construction

[0048] The core of the present application is to provide a malware detection method. Before describing the embodiment of the present application in detail, the malicious software detection method in the related art will be described first.

[0049] In related technologies, malware detection methods based on the Android system mainly include code feature-based detection methods and behavior analysis-based detection methods.

[0050] Among them, the code feature-based detection method operates by pattern matching the code set extracted from the Android software package. This method requires a complete software package code, and is relatively weak against increasingly diverse means of packing and camouflage. To detect new types of malicious code, it is necessary to manually extract new code features and add them to the matching set, which is cumbersome.

[0051] The detection method based on behavior analysis refers to the method of classifying the running records of the softwa...

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Abstract

The invention discloses a malicious software detection method. The method comprises the following steps: determining to-be-detected target software; obtaining a system call name and a network activityevent of the target software; sorting the system call names and the network activity events of the target software in a unified mode according to timestamps, and generating aggregation dynamic characteristics of the target software through encoding; inputting the aggregation dynamic characteristics of the target software into a pre-trained target neural network model based on a sequence converterstructure to obtain an output result; and determining whether the target software is malicious software or not according to the output result. By applying the technical scheme provided by the invention, the malicious software in the terminal is effectively detected by combining the system call name of the software and the network activity event and utilizing the structure of the sequence converter, so that the normal operation of the terminal is prevented from being influenced, and the user experience is improved. The invention further discloses a malicious software detection device which hasthe corresponding technical effects.

Description

technical field [0001] The present application relates to the field of computer application technology, and in particular to a malicious software detection method and device. Background technique [0002] With the rapid development of computer technology and terminal technology, terminals are more and more widely used in daily work and life. Various software can be installed in the terminal based on the Android system to meet the needs of users. Installing software in the terminal brings convenience to users, but also brings some security risks, because some malicious software may cause harm to the terminal. [0003] How to effectively detect malicious software in a terminal is a technical problem urgently needed to be solved by those skilled in the art. Contents of the invention [0004] The purpose of the present application is to provide a malware detection method and device, so as to effectively detect malware in a terminal and avoid affecting the normal operation of...

Claims

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Application Information

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IPC IPC(8): G06F21/56G06K9/62G06N3/04G06N3/08
CPCG06F21/566G06N3/08G06F2221/033G06N3/047G06N3/048G06N3/045G06F18/2415G06F18/241
Inventor 刘洋王轩龙瀚林田志成漆舒汉张加佳夏文唐琳琳
Owner HARBIN INST OF TECH SHENZHEN GRADUATE SCHOOL
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