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NIN neural network-based malicious code variation detection method

A malicious code and neural network technology, applied in biological neural network models, neural architectures, instruments, etc., can solve the problem of small image data, achieve the effects of improving performance, solving data imbalance, and suppressing useless information

Inactive Publication Date: 2018-01-19
BEIJING UNIV OF TECH
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Problems solved by technology

Secondly, in order to enable the NIN neural network to better extract the characteristics of the grayscale image generated by malicious code and solve the problem of too small image data (to avoid overfitting), it is proposed to use the data enhancement method to process the grayscale image in advance

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  • NIN neural network-based malicious code variation detection method
  • NIN neural network-based malicious code variation detection method
  • NIN neural network-based malicious code variation detection method

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Embodiment Construction

[0045] In order to make the object, technical solution and features of the present invention clearer, the present invention will be further described in detail below in conjunction with specific implementation examples and with reference to the accompanying drawings. The basic flow chart of the detection method for malicious code variants is as follows: figure 1 shown.

[0046] The individual steps are explained below:

[0047] 1) A method of processing malicious code and converting it into an uncompressed grayscale image is proposed, so that the original malicious code detection technology can be transformed into an image detection problem.

[0048] 2) Propose the use of data augmentation techniques to overcome the lack of data, and study the impact of different data augmentation combinations on the test results.

[0049] 3) A NIN neural network model for gray-scale image detection is proposed, which greatly speeds up the detection speed and effectively improves the detect...

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Abstract

The invention discloses an NIN neural network-based malicious code variation detection method, and belongs to a malicious code protection technology in the field of information safety. The method mainly comprises the following steps of: mapping a malicious code into a grayscale image; enhancing data; and designing a grayscale image detection-oriented NIN neural network. The method specifically comprises the following steps of: firstly, mapping a binary file of the malicious code into the uncompressed grayscale image through a corresponding method; secondly, in order to enable the NIN neural network to better extract features of the grayscale image generated by the malicious code and solving the problem that the image is too small in data scale, previously processing the grayscale image byusing a data enhancement method; and finally, carrying out training by using an NIN neural network model on the basis of existing data.

Description

technical field [0001] The invention belongs to the field of information security, in particular to a method for detecting malicious code variants based on a NIN neural network, which belongs to malicious code protection technology. Background technique [0002] With the vigorous development of the Internet, the scale of malicious codes has grown exponentially, and has become one of the key factors threatening Internet security. The China Internet Network Information Center (CNNIC) released the 39th "Statistical Report on Internet Development in China", which shows that the data shows that in 2016, the proportion of users who encountered network security incidents reached 70% of the total Internet users. Trojan horses are one of the top cybersecurity problems encountered by netizens. As of December 2016, the number of PCs infected with Trojan horse programs across the country was 247 million as monitored by 360 Security Center. As of December 2016, 360 Security Center has ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F21/56G06K9/62G06N3/04
Inventor 赵建峰宁振虎蔡永泉
Owner BEIJING UNIV OF TECH
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