The Similarity Analysis of Malicious Software

被引：6
|
作者：
Liu, Jing [1 ]
Wang, Yuan [1 ]
Wang, Yongjun [1 ]
机构：
[1] Natl Univ Def Technol, Coll Comp, Changsha, Hunan, Peoples R China
来源：
2016 IEEE FIRST INTERNATIONAL CONFERENCE ON DATA SCIENCE IN CYBERSPACE (DSC 2016) | 2016年
基金：
中国国家自然科学基金;
关键词：
Malicious software; similarity analysis; variants;
D O I：
10.1109/DSC.2016.12
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Malicious software poses a major threat to network security. The sheer volume of it is growing at an exponential pace. Researches have shown that the majority of new malicious samples are just variations of encountered malicious software. Therefore, similarity analysis has been put forward as an effective way to counteract the enormous new instances. Through measuring the similarity degree among instances, it can quickly identify malicious variants. In this paper, we provide an overview of algorithms used in similarity analysis of malicious software.
引用
收藏
页码：161 / 168
页数：8
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