Hend Faisal^1,2, Hanan Hindy¹, Samir Gaber^2,3, Abdel-Badeeh Salem³, ¹Ain Shams University, Egypt, ²Egyptian Computer Emergency and Readiness Team (EG-CERT), National Telecom Regulatory Authority (NTRA), Egypt, ³Helwan University, Egypt

The rapid evolution of technology in the past years largely contributed to the digital transformation, however, attackers took advantage of it to spread malicious software (malware). Nowadays, malware has become more sophisticated, which makes it harder to be detected with traditional techniques. Over the years, attacks became, not only limited to computer-based operating systems, but also to that of mobilebased, which makes it even harder for analysts. Furthermore, this increases the need for more research in this direction. The technological evolution also gives researchers the chance to utilize Artificial Intelligence widely and leverage its capabilities in many fields in general and in the field of malware detection in particular. This paper provides a literature review on malware detection using Artificial Intelligence techniques and specifically, Machine Learning and Deep Learning techniques. The paper helps researchers to have a broad idea of the latest malware detection techniques, available datasets, challenges, and limitations.

Malware Detection, Artificial Intelligence, Machine Learning, Deep Learning, Android Malware.