A Framework for Optimizing Malware Classification by Using Genetic Algorithm

• Published in: Software Engineering and Computer Systems pp. 58 - 72
• Main Authors: Yusoff, Mohd Najwadi, Jantan, Aman
• Format: Book Chapter
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg
• Series: Communications in Computer and Information Science
• Subjects: Genetic Algorithm; Malware Classification; Unique Malware
• ISBN: 3642221904; 9783642221903
• ISSN: 1865-0929; 1865-0937
• DOI: 10.1007/978-3-642-22191-0_5

Malware classification is a vital in combating the malware. Malware classification system is important and work together with malware identification to prepare the right and effective antidote for malware. Current techniques in malware classification do not give a good classification result when it deals with the new and unique types of malware. For this reason, we proposed the usage of Genetic Algorithm to optimize the malware classification system as well as help in malware prediction. The new malware classification system is based on malware target and its operation behavior. The result from this study will create a new framework that designed to optimize the classification of malware. This new malware classification system also has an ability to train and learn by itself, so that it can predict the current and upcoming trend of malware attack.