Malware Threat Assessment Using Fuzzy Logic Paradigm
Ekta Gandotra, Divya Bansal, Sanjeev Sofat · Cybernetics & Systems · 2016
Academicians and industrialists working on malware use static and dynamic analysis in order to understand their functionality and the menace level posed by them. Industries providing anti-malware solutions calculate malware threat level using the approaches that involve human intervention and demand the skilled analysts along with a large number of resources. With the increasing volume, velocity, and complexity of malware, assigning such a large number of resources is not possible. Thus, there is a need to develop techniques that can automatically compute the threat or damage posed by a piece of malware (to a victim machine) as soon as it appears in the wild. This assessment of damage capability level to a zero-day malware can help in providing early warnings about a specific piece of malware so that immediate attention could be paid to it in terms of allocating resources for performing a closer analysis. This paper presents an automated technique based on fuzzy modeling for computing damage potential of malicious programs, which is calculated on the basis of features obtained after performing automated analysis of malware binaries in the sandboxed environment.