AI-Enhanced Cybersecurity: Leveraging Artificial Intelligence for Threat Detection and Mitigation

Authors

  • Praveen Kumar Shukla and Dr C S Raghuvanshi and Dr Hari Om Sharan

Keywords:

Cybersecurity, Digital transformation, Cyber threats, Malicious intrusions, Artificial Intelligence (AI), Threat detection, Prevention mechanisms, Intrusion Prevention Systems (IPS), security best practices.

Abstract

This in-depth study offers a holistic perspective on cyber security strategies, placing a strong emphasis on the pivotal role of Intrusion Detection Systems (IDS) and proactive prevention mechanisms in the constantly shifting landscape of cyber threats. The journey begins with a detailed exploration of emerging cyber threats, ranging from zero-day vulnerabilities, AI-driven attacks, and IoT-based
vulnerabilities to the ever-intriguing world of Ransomware-as-a-Service (RaaS). A comprehensive understanding of these evolving threats is essential for organizations seeking to fortify their security measures in a world of perpetual digital transformation.

References

"A Survey of Deep Learning for Scientific Data Processing" by Samuel Kaski, Kärkkäinen, Proceedings of Tomi. the In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2018. DOI: 10.1007/978- 3-030-109288_1

"A Survey of Network Anomaly Detection Techniques" by Dhanabal L., Shantharajah S. in Journal of Network and Computer Applications, 60, 19-31, 2016. DOI: 10.1016/j.jnca.2016.02.015

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Published

2024-12-03

How to Cite

Praveen Kumar Shukla and Dr C S Raghuvanshi and Dr Hari Om Sharan. (2024). AI-Enhanced Cybersecurity: Leveraging Artificial Intelligence for Threat Detection and Mitigation. Journal of Computational Analysis and Applications (JoCAAA), 33(08), 2111–2123. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/1984

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Section

Articles