IJBTT

Applications of Generative AI for Scaling Security Teams
	© 2024 by IJCTT Journal
	Volume-72 Issue-6
	Year of Publication : 2024
	Authors : Prahathess Rengasamy
	DOI :  10.14445/22312803/IJCTT-V72I6P111

How to Cite?

Prahathess Rengasamy, "Applications of Generative AI for Scaling Security Teams," International Journal of Computer Trends and Technology, vol. 72, no. 6, pp. 80-83, 2024. Crossref, https://doi.org/10.14445/22312803/IJCTT-V72I6P111

Abstract
In the contemporary cybersecurity landscape, characterized by an escalating volume and sophistication of threats, an imperative exists for scalable and efficient security operations. Traditional security teams frequently encounter limitations in managing the complexity and sheer volume of security incidents. This paper investigates the application of generative Artificial Intelligence (AI) as a transformative solution for enhancing and scaling security teams’ capabilities. Generative AI, distinguished by its capacity to learn from extensive datasets and generate novel insights, presents a promising avenue for augmenting human expertise in areas such as threat detection, response, and prevention. Through the automation of routine tasks, the generation of predictive analytics, and the provision of real-time threat intelligence, generative AI can substantially improve the operational efficacy of security teams. This paper examines the methodologies for integrating generative AI into existing security infrastructures, evaluates the benefits and challenges associated with such integration, and presents case studies that illustrate the practical impact of generative AI in security operations. The findings underscore the transformative potential of generative AI in fostering more agile, proactive, and resilient security practices, thereby addressing the pressing demands of modern cybersecurity environments.

Keywords
Generative Artificial Intelligence, Cybersecurity, Product security, Cloud security, Compliance.

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