1 Department of Management, Indiana Wesleyan University USA.
2 Department of Mechanical Engineering, Jomo Kenyatta University of Agriculture and Technology, Kenya.
Review Article
World Journal of Advanced Research and Reviews, 2024, 21(01), 2584-2598
Received on 14 December 2023; revised on 22 January 2024; accepted on 25 January 2024
The rapid evolution of information and communication technologies, notably the Internet, has yielded substantial benefits while posing challenges to information system security. With an increasing frequency of cyber threats—from unauthorized access to data breaches—the digital landscape's vulnerability is evident. Addressing the financial impact of cybercrime, this study delves into the role of Artificial Intelligence (AI) and Machine Learning (ML) technologies in cybersecurity. Analyzing advancements and outcomes, the research explores practical techniques for anomaly detection, threat prediction, and automated response. By investigating prior research and real-world implementations, the study provides valuable insights into the potential of AI/ML, uncovering current trends, challenges, and prospects in enhancing cybersecurity tactics amid a dynamically changing threat landscape.
Information security; Cybercrime; Cybersecurity; Artificial Intelligence (AI); Machine Learning (ML); Anomaly detection; Threat prediction; Automated response
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Olakunle Abayomi Ajala and Olusegun Abiodun Balogun. Leveraging AI/ML for anomaly detection, threat prediction, and automated response. World Journal of Advanced Research and Reviews, 2024, 21(1), 2584-2598. Article DOI: https://doi.org/10.30574/wjarr.2024.21.1.0287