Publication Type : Journal Article
Publisher : Journal of Intelligent & Fuzzy Systems, IOS Press
Source : Journal of Intelligent & Fuzzy Systems, IOS Press, Volume 38, Issue 5, p.6517 - 6526 (2020)
Url : https://content.iospress.com/articles/journal-of-intelligent-and-fuzzy-systems/ifs179732
Keywords : Anti-malware research, Cyber security, Evolutionary algorithms, malware, malware creation, virus
Campus : Coimbatore
School : School of Engineering
Department : Computer Science
Year : 2020
Abstract : This paper attempts to employ Evolutionary Algorithm(EA) techniques to evolve variants of a computer virus(Timid ) that successfully evades popular antivirus scanners. Generating authentic variants of a specific malware results in a valid database of malware variants, which is sought by anti-malware scanners, so as to identify the variants before they are released by malware developers. This preliminary investigation applies EAs to mutate the Timid virus with a simple code evasion strategy, i.e., insertion and deletion(if available) of a specific assembly code instruction directly into the virus source code. Starting with a database of over 60 popular antivirus scanners, this EA based approach for malware variant generation successfully evolves Timid variants that evade more than 97% of the antivirus scanners. The results from these preliminary investigations demonstrate the potential for EA based malware generation and also opens up avenues for further analysis.
Cite this Research Publication : Ritwik Murali and Dr. Shunmuga Velayutham C., “A preliminary investigation into automatically evolving computer viruses using evolutionary algorithms”, Journal of Intelligent & Fuzzy Systems, vol. 38, no. 5, pp. 6517 - 6526, 2020.