AI-Powered Cloud Security: Leveraging Advanced Threat Detection for Maximum Protection

Bolanle, Oluwapailerin and Bamigboye, Kehinde (2019) AI-Powered Cloud Security: Leveraging Advanced Threat Detection for Maximum Protection. International Journal of Trend in Scientific Research and Development, 3 (2). pp. 1407-1412. ISSN 2456-6470

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Abstract

In today's rapidly evolving digital landscape, organizations are increasingly migrating to the cloud, making robust security measures more crucial than ever. This article delves into the transformative potential of AI-powered cloud security, focusing on how advanced threat detection technologies can enhance protection against a myriad of cyber threats. By integrating artificial intelligence with cloud security frameworks, organizations can proactively identify and respond to vulnerabilities in real time, significantly reducing the risk of data breaches and compliance violations. We explore various AI-driven techniques, including machine learning algorithms, behavioral analytics, and anomaly detection, that empower security teams to detect threats with unprecedented accuracy and speed. Furthermore, the article highlights best practices for implementing AI solutions within existing cloud security architectures, ensuring a seamless transition while maximizing protection. Through case studies and expert insights, we demonstrate the efficacy of AI-powered security measures in real-world scenarios, underscoring their role in shaping the future of cybersecurity. Ultimately, this article aims to equip organizations with the knowledge and strategies necessary to leverage AI for enhanced cloud security, fostering resilience in an increasingly complex threat landscape.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Divisions:	Postgraduate > Master's of Islamic Education
Depositing User:	Journal Editor
Date Deposited:	24 Oct 2024 05:22
Last Modified:	24 Oct 2024 05:22
URI:	http://eprints.umsida.ac.id/id/eprint/14292

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