Exploring the Landscape: A Systematic Review of Artificial Intelligence Techniques in Cybersecurity
Md. Kamruzzaman, Md Khokan Bhuyan, Rakibul Hasan, Syeda Farjana Farabi, Sadia Islam Nilima, Md. Sazzad Hossain · 2024
In today's interconnected world, the dissemination of vast amounts of information through the internet has become ubiquitous, facilitating seamless communication and connectivity across the globe. However, this digital landscape is fraught with cybersecurity threats, posing significant challenges to individuals, businesses, and organizations alike. In response to these evolving risks, there has been a burgeoning interest in leveraging machine learning techniques to bolster cybersecurity defenses. Through a meticulous examination of 736 research papers spanning from 2012 to 2024, our comprehensive analysis identified 501 pertinent works, shedding light on the recent trends in this critical research domain. By deploying a systematic literature review (SLR) we categorize these papers based on implementation methodologies, article types, publishers, and efficacy, and offer a coherent and visually informative representation of the landscape. This endeavor underscores the immense potential of machine learning in fortifying cybersecurity measures and serves as a valuable resource for researchers, students, publishers, and industry experts seeking to navigate and contribute to the dynamic field of machine learning for cybersecurity.