TITLE:
A Comparison of Malware Detection Techniques Based on Hidden Markov Model
AUTHORS:
Saja Alqurashi, Omar Batarfi
KEYWORDS:
Malware, HMM, Detection Tool, Obfuscation Techniques, Metamorphic
JOURNAL NAME:
Journal of Information Security,
Vol.7 No.3,
April
22,
2016
ABSTRACT: Malware is a software which is designed with an intent to damage a
network or computer resources. Today, the emergence of malware is on boom letting
the researchers develop novel techniques to protect computers and networks. The
three major techniques used for malware detection are heuristic, signature-based,
and behavior based. Among these, the most prevalent is the heuristic based
malware detection. Hidden Markov Model is the most efficient technique for malware
detection. In this paper, we present the Hidden Markov Model as a cutting edge
malware detection tool and a comprehensive review of different studies that
employ HMM as a detection tool.