Autonomous Threat Response using Predictive Analytics for Intelligent Enterprise Cloud Security Operations
Abstract
The rapid adoption of enterprise cloud environments has expanded the digital attack surface and introduced increasingly complex cybersecurity challenges. Traditional security operations, which rely heavily on rule-based detection and manual incident response, often struggle to identify sophisticated threats quickly enough to prevent significant damage. Autonomous threat response supported by predictive analytics offers an emerging approach for improving the speed, accuracy, and adaptability of cloud security operations. This paper examines how predictive analytics, machine learning, behavioral analysis, and automated response mechanisms can be integrated into intelligent enterprise cloud security operations. The proposed approach uses historical security events, real-time telemetry, user and entity behavior, network activity, identity information, and workload characteristics to identify patterns associated with potential attacks and predict emerging threats. Predictive models can support early detection of anomalies, prioritize security alerts, estimate threat severity, and initiate predefined response actions while maintaining appropriate human oversight. The methodology considers data collection, preprocessing, feature engineering, predictive modeling, threat classification, autonomous response, and performance evaluation. Particular attention is given to reducing false positives, improving response time, maintaining explainability, and addressing privacy and governance requirements. The study argues that predictive and autonomous capabilities can strengthen cloud security operations when implemented through controlled automation, continuous monitoring, model validation, and human-centered security governance
Article Information
Journal |
International Journal of Emerging Trends in Engineering and Management Research |
|---|---|
Volume (Issue) |
Vol. 8 No. 6 (2023): International Journal of Emerging Trends in Engineering and Management Research (IJETEMR) |
DOI |
|
Pages |
14729-14736 |
Published |
November 12, 2023 |
| Copyright |
All rights reserved |
Open Access |
This work is licensed under a Creative Commons Attribution 4.0 International License. |
How to Cite |
Dr. Sakinat Oluwabukonla Folorunso (%2023). Autonomous Threat Response using Predictive Analytics for Intelligent Enterprise Cloud Security Operations. International Journal of Emerging Trends in Engineering and Management Research , Vol. 8 No. 6 (2023): International Journal of Emerging Trends in Engineering and Management Research (IJETEMR) , pp. 14729-14736. https://doi.org/10.15662/ijetemr.2023.0806006 |
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