AI-Driven Cybersecurity: Proactive Threat Detection and Intelligent Response Systems

Authors

  • Rahul Reddy Bandhela

Keywords:

AI-driven cybersecurity, threat detection, machine learning, anomaly detection, risk mitigation.

Abstract

With growing threats, traditional methods of Security are no longer enough to guarantee protection for modern day digitalinfrastructures. AI-driven Cybersecurity: Proactive threat detection and intelligent response systems powered by machinelearning (ML) and artificial intelligence (AI) techniques. These systems can assess potential threats and analyze data forpatterns, alerting users of suspicious activity

References

Buczak, A. L., & Guven, E. (2016). A survey of data mining and machine learning methods for cyber security intrusion detection. IEEE Communications Surveys & Tutorials, 18(2), 1153-1176.

Saxe, J. B., & Berlin, M. (2017). Deep learning for malware classification: Insights and challenges. Proceedings of the 5th International Conference on Cyber Security and Protection of Digital Services, 42-52.

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Published

2020-06-20

How to Cite

Rahul Reddy Bandhela. (2020). AI-Driven Cybersecurity: Proactive Threat Detection and Intelligent Response Systems . Journal of Computational Analysis and Applications (JoCAAA), 28(6), 66–73. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/3456

Issue

Section

Articles