Literature Review of Visualizing and Detecting Malware

Zhaoheng Yin

doi:10.47297/taposatWSP2633-456921.20230402

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Literature Review of Visualizing and Detecting Malware

4卷第2期

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Literature Review of Visualizing and Detecting Malware
Literature Review of Visualizing and Detecting Malware
School of Electrical Engineering and Computer Science, University of Ottawa,, ON,Ottawa,Canada,K1N 6N5
2023年4卷第2期页码：137-142
纸质出版日期： 2023 ，
DOI：10.47297/taposatWSP2633-456921.20230402
Accepted：

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(2023). Literature Review of Visualizing and Detecting Malware. 科技理论与实践（英文版）, 4(2), 137-142.

Zhaoheng Yin. (2023). Literature Review of Visualizing and Detecting Malware. Theory and Practice of Science and Technology, 4(2), 137-142.
(2023). Literature Review of Visualizing and Detecting Malware. 科技理论与实践（英文版）, 4(2), 137-142. DOI： 10.47297/taposatWSP2633-456921.20230402.

Zhaoheng Yin. (2023). Literature Review of Visualizing and Detecting Malware. Theory and Practice of Science and Technology, 4(2), 137-142. DOI： 10.47297/taposatWSP2633-456921.20230402.

摘要

Abstract

Visualization detection is an emerging technology by extracting the characteristics of malware image performance

has solved the traditional detection technology can not accurately detect the unknown malicious code problem

the method has received more and more attention

especially in the context of the continuous development of anti-detection technology

this paper on the different types of malware code visualization detection methods to conduct a comprehensive research and analysis from the grayscale image transformation

machine learning visualization Deep Learning Visualization and Hybrid Detection

summarizes and analyzes the current problems and future development direction of visual detection

aiming to help scholars improve the accuracy and efficiency of visual detection methods.

关键词

Keywords

Visualizing detectionMalwareDeep leaningMachine learning

references

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