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Finding New Varieties of Malware with the Classification of Network Behavior
Mitsuhiro HATADA Tatsuya MORI
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2017/08/01
Online ISSN: 1745-1361
Type of Manuscript: Special Section PAPER (Special Section on Information and Communication System Security)
Category: Program Analysis
malware communication model, clustering analysis, network behavior classification, new varieties of malware,
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An enormous number of malware samples pose a major threat to our networked society. Antivirus software and intrusion detection systems are widely implemented on the hosts and networks as fundamental countermeasures. However, they may fail to detect evasive malware. Thus, setting a high priority for new varieties of malware is necessary to conduct in-depth analyses and take preventive measures. In this paper, we present a traffic model for malware that can classify network behaviors of malware and identify new varieties of malware. Our model comprises malware-specific features and general traffic features that are extracted from packet traces obtained from a dynamic analysis of the malware. We apply a clustering analysis to generate a classifier and evaluate our proposed model using large-scale live malware samples. The results of our experiment demonstrate the effectiveness of our model in finding new varieties of malware.