Anti-obfuscation techniques: Recent analysis of malware detection

• Main Authors: Gorment, Nor Zakiah, Selamat, Ali, Krejcar, Ondrej
• Format: Conference or Workshop Item
• Published: 2022
• Subjects: QA76 Computer software
• Online Access: http://eprints.utm.my/id/eprint/100542/; http://dx.doi.org/10.3233/FAIA220249

One of the challenging issues in detecting the malware is that modern stealthy malware prefers to stay hidden during their attacks on our devices and be obfuscated. They can evade antivirus scanners or other malware analysis tools and might attempt to thwart modern detection, including altering the file attributes or performing the action under the pretense of authorized services. Therefore, it's crucial to understand and analyze how malware implements obfuscation techniques to curb these concerns. This paper is dedicated to presenting an analysis of anti-obfuscation techniques for malware detection. Furthermore, an empirical analysis of the performance evaluation of malware detection using machine learning algorithms and the obfuscation techniques was conducted to address the associated issues that might help researchers plan and generate an efficient algorithm for malware detection.