Semantics-aware malware detection

被引:319
作者
Christodorescu, M [1 ]
Jha, S [1 ]
Seshia, SA [1 ]
Song, D [1 ]
Bryant, RE [1 ]
机构
[1] Univ Wisconsin, Madison, WI 53706 USA
来源
2005 IEEE SYMPOSIUM ON SECURITY AND PRIVACY, PROCEEDINGS | 2005年
关键词
D O I
10.1109/SP.2005.20
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A malware detector is a system that attempts to determine whether a program has malicious intent. In order to evade detection, malware writers (hackers) frequently use obfuscation to morph malware. Malware detectors that use a pattern-matching approach (such as commercial virus scanners) are susceptible to obfuscations used by hackers. The fundamental deficiency in the pattern-matching approach to malware detection is that it is purely syntactic and ignores the semantics of instructions. In this paper we present a malware-detection algorithm that addresses this deficiency by incorporating instruction semantics to detect malicious program traits. Experimental evaluation demonstrates that our malware-detection algorithm can detect variants of malware with a relatively low run-time overhead Moreover, our semantics-aware malware detection algorithm is resilient to common obfuscations used by hackers.
引用
收藏
页码:32 / 46
页数:15
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