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Stream/Area:
-
Subject:
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Paper ID:
10.55041/IJSREM.NCET011
Volume:
10 |
10 |
Oct 2026
Pages:
1-5
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Computer Science & Engineering
Ayya Nadar Janaki Ammal Collage
Computer Science & Engineering
Ayya Nadar Janaki Ammal Collage
Computer Science & Engineering
Ayya Nadar Janaki Ammal Collage
Computer Science & Engineering
Ayya Nadar Janaki Ammal Collage
As organizations rapidly migrate to complex multi-cloud environments, modern cyber threats have outpaced traditional, reactive security defenses. Addressing these challenges requires integrating Artificial Intelligence (AI) into next-generation cloud security frameworks. This paper explores how AI transforms modern cloud defense through core capabilities such as Anomaly & Behavioral Analytics, Predictive Threat Intelligence, Automated Threat Response, and dynamic Misconfiguration Detection. By continuously analyzing vast streams of cloud telemetry, AI systems identify subtle deviations from baseline behavior and fix exposure points before exploitation occurs. Furthermore, we examine the practical application of current market-leading AI tools, with a specific focus on Explainable AI (XAI) in platforms like Palo Alto Networks (Cortex XSIAM). XAI bridges the gap between complex machine learning decisions and human security analysts, providing transparent, interpretable insights that directly combat severe alert fatigue. Ultimately, this study demonstrates how combining automated response, predictive analytics, and explainable AI models defines the roadmap for next-generation cloud security—enabling proactive, efficient, and resilient security operations (SecOps).
KEYWORDS
The rapid escalation of multi-cloud complexity and cyber threat sophistication has rendered traditional, reactive security paradigms obsolete. Artificial Intelligence—specifically when combined with Explainable AI (XAI) and autonomous response frameworks—defines the future roadmap for resilient cloud defense. By continuously evaluating behavioral baselines, predicting attack vectors, auto-remediating misconfigurations, and providing transparent reasoning through platforms like Cortex XSIAM, AI transforms SecOps from an overloaded reactive function into a proactive, machine-speed defense core.
[1] Palo Alto Networks. (2024). Cortex XSIAM: The AI-Driven SOC Platform Technical Whitepaper. [2] Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press. [3] Vaswani, A. et al. (2017). Attention Is All You Need. Advances in Neural Information Processing Systems (NeurIPS). [4] Gartner Research. (2025). Emerging Technologies: Future of AI in Cloud Security Posture Management. [5] MITRE Corporation. (2024). MITRE ATT&CK for Cloud Matrix v14. Enterprise Framework. [6] Ribeiro, M. T., Singh, S., & Guestrin, C. (2016). 'Why Should I Trust You?': Explaining the Predictions of Any Classifier. ACM SIGKDD. [7] Grand View Research. (2025). Artificial Intelligence in Cybersecurity Market Size, Share & Trends Analysis Report, 2026–2033.
Publication Date
10/5/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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