Research on Malware Variant Detection Based on Global Texture Features
Hui Ling Guo, Jiangtao Wu, Shuguang Huang, Zulie Pan, Fan Shi, Zhi‐Hao Yan · 2020
How to quickly and efficiently detect malware variant information is of great research value in the field of malware detection. Based on the code visualization method, a detection method for malware variant families based on global texture features is proposed. By combining image feature processing technology and based on the global texture feature algorithm, we propose a method to detect malware variant families and test it on the malware variant data set. The experimental results show that the proposed method has good identification ability and practical application value of the malware variant family, and the detection accuracy and robustness have a certain improvement compared with existing research.