AI-Driven Cloud Security: Proactive Defense Against Evolving Cyber Threats

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Proactive Defense Against Evolving Cyber Threats</title> <meta name="description" content="AI-Driven Cloud Security: Proactive Defense Against Evolving Cyber Threats"> <meta name="keywords" content="Machine Learning, Natural Learning Processing, Denial-of-Service attacks, Sentiment Analysis, Cloud computing."> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <meta name="citation_title" content="AI-Driven Cloud Security: Proactive Defense Against Evolving Cyber Threats"> <meta name="citation_author" content="Ashly Joseph"> <meta name="citation_publication_date" content="2024/05/08"> <meta name="citation_journal_title" content="International Journal of Computer and Information Engineering"> <meta name="citation_volume" content="18"> <meta name="citation_issue" content="5"> <meta name="citation_firstpage" content="261"> <meta name="citation_lastpage" content="265"> <meta name="citation_pdf_url" 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enterprises and organizations globally in the current era of digital technology. The cloud has a multitude of advantages, including scalability, flexibility, and cost-effectiveness, rendering it an appealing choice for data storage and processing. The increasing storage of sensitive information in cloud environments has raised significant concerns over the security of such systems. The frequency of cyber threats and attacks specifically aimed at cloud infrastructure has been increasing, presenting substantial dangers to the data, reputation, and financial stability of enterprises. Conventional security methods can become inadequate when confronted with ever intricate and dynamic threats. Artificial Intelligence (AI) technologies possess the capacity to significantly transform cloud security through their ability to promptly identify and thwart assaults, adjust to emerging risks, and offer intelligent perspectives for proactive security actions. The objective of this research study is to investigate the utilization of AI technologies in augmenting the security measures within cloud computing systems. This paper aims to offer significant insights and recommendations for businesses seeking to protect their cloud-based assets by analyzing the present state of cloud security, the capabilities of AI, and the possible advantages and obstacles associated with using AI into cloud security policies.</p> <iframe src="https://publications.waset.org/10013632.pdf" style="width:100%; height:400px;" frameborder="0"></iframe> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Machine%20Learning" title="Machine Learning">Machine Learning</a>, <a href="https://publications.waset.org/search?q=Natural%20Learning%20Processing" title=" Natural Learning Processing"> Natural Learning Processing</a>, <a href="https://publications.waset.org/search?q=Denial-of-Service%20attacks" title=" Denial-of-Service attacks"> Denial-of-Service attacks</a>, <a href="https://publications.waset.org/search?q=Sentiment%20Analysis" title=" Sentiment Analysis"> Sentiment Analysis</a>, <a href="https://publications.waset.org/search?q=Cloud%20computing." title=" Cloud computing."> Cloud computing.</a> </p> <a href="https://publications.waset.org/10013632/ai-driven-cloud-security-proactive-defense-against-evolving-cyber-threats" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10013632/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10013632/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10013632/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10013632/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10013632/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10013632/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10013632/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10013632/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10013632/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10013632/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10013632.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">186</span> </span> <p class="card-text"><strong>References:</strong></p> <br>[1] Yaseen, Q., & Panda, B. (2012). Tackling insider threat in cloud relational databases. In 2012 IEEE Fifth International Conference on Utility and Cloud Computing (pp. 215-218). IEEE <br>[2] A. Gordon, The S cloud security professional. IEEE Cloud Comput. 3(1), 82–86 (2016). https://doi.org/10.1109/MCC.2016.21 <br>[3] Joseph, A. (2023). 'Demystifying Full-Stack Observability: Mastering Visibility, Insight, and Action in the Modern Digital Landscape'. World Academy of Science, Engineering and Technology, Open Science Index 200, International Journal of Computer and Information Engineering, 17(8), 485 - 492. <br>[4] De Oliveira, P. A. (2017). Predictive analysis of cloud systems. In 2017 IEEE/ACM 39th International Conference on Software Engineering Companion (ICSE-C) (pp. 483-484). IEEE. <br>[5] Sowmya, S. K., Deepika, P., & Naren, J. (2014). Layers of cloud–IaaS, PaaS and SaaS: a survey. International Journal of Computer Science and Information Technologies, 5(3), 4477-4480. <br>[6] Paulose, Jithu (2020). Innovative application of Additive Manufacturing in Biomedical Healthcare Technologies. International Journal of Advanced Research Trends in Engineering and Technology (IJARTET) Vol. 7, Issue 5. <br>[7] Joseph, A. (2023). 'A Holistic Framework for Unifying Data Security and Management in Modern Enterprises'. World Academy of Science, Engineering and Technology, Open Science Index 202, International Journal of Social and Business Sciences, 17(10), 596 - 603. <br>[8] Yasavur, U., Travieso, J., Lisetti, C., & Rishe, N. D. (2014, May). Sentiment analysis using dependency trees and named-entities. In The Twenty-Seventh International Flairs Conference. <br>[9] A. Qayyum et al (2020), Securing machine learning in the cloud: a systematic review of cloud machine learning security. Front. Big Data 3 https://doi.org/10.3389/fdata.2020.587139 <br>[10] M. C. Horowitz, G. C. Allen, E. Saravalle, A. Cho, K. Frederick, and P. Scharre (2018), Artificial intelligence and international security. Center for a New American Security. <br>[11] S. Guha, S.S. Yau, A.B. Buduru, Attack detection in cloud infrastructures using artificial neural network with genetic feature selection, in 2016 IEEE 14th International Conference on Dependable, Autonomic and Secure Computing (2016), pp. 414–419. https://doi.org/10.1109/DASC-PICom-DataCom-CyberSciTec.2016.32 <br>[12] Abraham, Sherly. Exploring the effectiveness of information security training and persuasive messages. Diss. University at Albany. 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AI-Driven Cloud Security: Proactive Defense Against Evolving Cyber Threats