AI-Enhanced Cyber Threat Detection

© 2024 by IJCTT Journal
Volume-72 Issue-6
Year of Publication : 2024
Authors : Sai Kiran Arcot Ramesh
DOI :  10.14445/22312803/IJCTT-V72I6P109

How to Cite?

Sai Kiran Arcot Ramesh, "AI-Enhanced Cyber Threat Detection," International Journal of Computer Trends and Technology, vol. 72, no. 6, pp. 64-71, 2024. Crossref,

Cybersecurity paradigms have taken a transformative shift with the advent of AI-Enhanced Cyber Threat Detection, which helps to enhance organizational security through advanced algorithms. This research paper delves into the proactive stance of Artificial Intelligence (AI) driven detection systems that sift through huge volumes of data on their own to recognize patterns indicative of cyber intrusions and attacks. By well-organized threat detection and incident response processes, these systems reduce the workloads for human analysts thus enabling them to concentrate on strategic decision-making and mitigation strategies. In addition, real-time monitoring of network operations is made easier using AI-based detection, which reduces dwell time and improves operational efficiency. Another way in which this can be achieved is by integrating other cybersecurity technologies, such as threat intelligence platforms with AI or Security Orchestration, Automation, and Response (SOAR) systems. Nevertheless, challenges like adversarial attacks, as well as ethical considerations show that further research must be conducted in this field and collaboration enhanced so as to strengthen AI-enabled cyber threat detection. This article, therefore, highlights the significance of proactive cybersecurity measures together with collaborative defense approaches in protecting digital assets against contemporary e-crimes.

Artificial Intelligence, Cyber Threat Detection, Cybersecurity, Machine Learning, Threat Intelligence, Incident Response, Security Orchestration, Automation and Response (SOAR), Adversarial Attacks, Ethical Considerations, Collaborative Defense Strategies.


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