M. Mohsin Raza1,#, Muhammad Umair1,#, Imran Arshad Choudhry1, Muhammad Qasim1, Muhammad Tahir Naseem2,*, Mamoona Naveed Asghar3, Daniel Gavilanes4,5,6,7, Manuel Masias Vergara4,8,9, Imran Ashraf10,*
CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.3, 2026, DOI:10.32604/cmes.2025.074164
- 30 March 2026
Abstract Over the past decade, the landscape of cybersecurity has been increasingly shaped by the growing sophistication and frequency of malware attacks. Traditional detection techniques, while still in use, often fall short when confronted with modern threats that use advanced evasion strategies. This systematic review critically examines recent developments in malware detection, with a particular emphasis on the role of artificial intelligence (AI) and machine learning (ML) in enhancing detection capabilities. Drawing on literature published between 2019 and 2025, this study reviews 105 peer-reviewed contributions from prominent digital libraries including IEEE Xplore, SpringerLink, ScienceDirect, and ACM… More >