Research on N-gram-based malicious code feature extraction algorithm
Fang Luo, Qingyu Ou, Wei Guoheng · 2010
The amount of computer virus is on the increase since its first appearance and has posed serious security threats to the computer systems. Most of the current anti-virus systems attempt to detect these new malicious programs through heuristics scheme, but this costs a lot and is often ineffective. In this paper, an N-gram-based malicious code feature extraction algorithm, based on statistical language model, is presented. Through this algorithm, the N-gram features of the sample set can be extracted and the features of the malicious code can be obtained exactly. Compared with the traditional feature code-based approaches, our approach has higher detection rates for new malicious codes.