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A malware image format detection method and device based on deep learning

A malicious software and image format technology, applied in computer security devices, computer components, character and pattern recognition, etc., can solve the problems of discrete original data and low precision of traditional malware detection, and achieve good detection results and good Applicability and accuracy, the effect of improving accuracy

Active Publication Date: 2021-06-08
ZHEJIANG UNIV OF TECH
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AI Technical Summary

Problems solved by technology

[0005] In order to overcome the disadvantages of discrete and difficult processing of malware raw data and low accuracy of traditional malware detection, the present invention provides a malware image format detection method based on deep learning and its device with high precision and improved original sample processing method

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  • A malware image format detection method and device based on deep learning
  • A malware image format detection method and device based on deep learning
  • A malware image format detection method and device based on deep learning

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Embodiment Construction

[0058] The present invention will be further described below in conjunction with the accompanying drawings.

[0059] In the first aspect, the embodiment of the present invention provides a method for detecting malware image formats based on deep learning, please refer to figure 1 , including the following steps:

[0060] 1) Obtain a malware sample data set; specifically include:

[0061] 1.1) Obtained 9 malware family sample data sets, a total of 10868 malware samples, and the data is saved in the assembly language file type with the suffix ".asm";

[0062] 1.2) Considering the difference in the number of samples of each category and for the convenience of subsequent work, the data sets of each category are divided into a proportion of about 80% of the training set and about 20% of the test set. The training set has a total of 8694 samples, and the test set A total of 2174 samples;

[0063] 2) Convert to malware image format; refer to figure 2 , including:

[0064] 2.1) ...

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Abstract

A method for detecting malware image formats based on deep learning, comprising the following steps: 1) constructing a malware sample dataset; 2) converting to malware image formats; 3) constructing a convolutional neural network classifier; 4) according to the sample The dataset trains a classifier to classify malware samples. The present invention also provides a device for implementing a method for detecting malware image formats based on deep learning. The invention has good applicability and precision, can effectively detect malicious software, and obtains better detection effect.

Description

technical field [0001] The invention belongs to the technical field of network space security, and designs a method and a device for detecting malware image formats based on deep learning. Background technique [0002] With the rapid development of computers and the Internet, communication between people has become more and more convenient, and network information exchange and intelligent applications play a vital role in people's daily life. According to statistics, as of June 2016, the number of people using the Internet in the world has reached more than 3.6 billion, accounting for more than half of users for the first time. At the same time, the development of the network is also accompanied by many network security problems, and malicious software is one of the important influencing factors. Malware (MaliciousSoftware, Malware) refers to a software program that purposely enables an attacker to damage a computer, server, client, or computer network. Representative type...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F21/56G06K9/62
CPCG06F21/563G06F2221/033G06F18/24G06F18/214
Inventor 陈晋音邹健飞袁俊坤
Owner ZHEJIANG UNIV OF TECH