Abstract
The aim of this article is to present an approach to develop and verify a method of formal modeling of cyber threats directed at computer systems. Moreover, the goal is to prove that the method enables one to create models resembling the behavior of malware that support the detection process of selected cyber attacks and facilitate the application of countermeasures. The most common cyber threats targeting end users and terminals are caused by malicious software, called malware. The malware detection process can be performed either by matching their digital signatures or analyzing their behavioral models. As the obfuscation techniques make the malware almost undetectable, the classic signature-based anti-virus tools must be supported with behavioral analysis. The proposed approach to modeling of malware behavior is based on colored Petri nets. This article is addressed to cyber defense researchers, security architects and developers solving up-to-date problems regarding the detection and prevention of advanced persistent threats.
Highlights
According to the numerous cyber security reports, the number of cyber threats is increasing rapidly from 23,680,646 in 2008 [1] to 5,188,740,554 in 2013 [2]
We prove that the method enables one to create models resembling the behavior of malware, and these models support the detection of cyber threats directed at computer systems
The article tackles the problem of malware modeling for the purpose of the detection process
Summary
According to the numerous cyber security reports, the number of cyber threats is increasing rapidly from 23,680,646 in 2008 [1] to 5,188,740,554 in 2013 [2]. This is nowadays one of the most vexing. According to this report, about 30% of organizations are systematically infected by malware. The reason for this situation is not, as it might be expected, the inappropriate update of operating systems and virus definition files, but the lack of all signatures for existing and appearing threats
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