1 Department of Computer Science, Louisiana State University Shreveport, Shreveport, USA.
2 Computer Science and Engineering, Stamford University Bangladesh.
3 SBIT Inc., USA.
4 Department of Computer Science and Engineering, Daffodil International University Dhaka Bangladesh.
Received on 13 June 2022; revised on 26 July 2022; accepted on 28 July 2022
This research investigates how Artificial Intelligence (AI) supports predictive cybersecurity by analyzing behavior to recognize and block upcoming cyberattacks. Due to the increasing difficulty of cyber-attacks, age-old reactive approaches to cybersecurity are inadequate. The research relies on machine learning algorithms and behavioral analytics to test their ability to find anomalies and predict attacks. After observing data, conducting case studies, and reviewing models, the study finds that AI can make early threat detection more accurate, lower the number of false alarms, and quicken response times. The study found that AI can bolster cybersecurity systems by bringing forward automatic defenses. It is argued in this paper that including AI-powered predictive approaches in system security can make them more efficient and safe. Results suggest areas where further study can help AI prediction systems work better and process more cases.
AI cybersecurity; Predictive analytics; Behavioral analytics; Threat detection; Machine learning; Anomaly detection
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Kailash Dhakal, Mohammad Mosiur Rahman, Kairul Anam, Mashfiquer Rahman, Ramesh Poudel and Mostafizur Rahman. The role of AI in predictive cybersecurity. World Journal of Advanced Engineering Technology and Sciences, 2022, 06(02), 147-157. Article DOI: https://doi.org/10.30574/wjaets.2022.6.2.0094