Articles Open Access
Intelligent Cloud Security through Continuous Threat Detection and Risk Assessment
Principal Consultant, Oracle Financial Service Software Ltd, Bengaluru, India
Abstract
Cloud computing has transformed the way organizations store, process, and manage information by providing scalable, flexible, and cost-effective computing resources. However, the increasing dependence on cloud environments has also expanded the attack surface, exposing organizations to sophisticated cyber threats, data breaches, insider attacks, malware, ransomware, and configuration vulnerabilities. Traditional security mechanisms that rely on periodic monitoring and signature-based detection are no longer sufficient to address the dynamic nature of modern cloud infrastructures. Intelligent cloud security integrates artificial intelligence (AI), machine learning (ML), behavioral analytics, and continuous monitoring to proactively detect threats and assess security risks in real time. Continuous threat detection enables organizations to identify abnormal activities, unauthorized access attempts, and emerging attack patterns before they cause significant damage. Simultaneously, continuous risk assessment evaluates vulnerabilities, security configurations, compliance status, and asset criticality to prioritize mitigation strategies. This integrated approach improves security resilience by reducing response time, minimizing false positives, and supporting automated incident response. Furthermore, intelligent cloud security enhances regulatory compliance and business continuity by enabling adaptive security policies based on evolving threat intelligence. This study explores the significance of intelligent cloud security through continuous threat detection and risk assessment, reviews existing literature, discusses an appropriate research methodology, and highlights how intelligent technologies contribute to strengthening cloud security frameworks against evolving cyber threats
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Publication Information
| Journal | International Research Journal of Innovative Engineering |
|---|---|
| Volume | 7 |
| Number | 6 |
| Pages | 13571-13581 |
| Published | 2023-11-10 |
| Issue | Vol. 7 No. 6 (2023): International Research Journal of Innovative Engineering (IRJIE) |
References
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31. Gandikota, S. P. (2023). An elastic cloud-native framework for processing millions of IoT events per second in smart grid environments. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(1), 8049–8063. https://doi.org/10.15662/IJRPETM.2023.0601006
32. Mohammed, S. (2022). Designing secure zero trust architectures for global enterprise environments. International Journal of Science, Research and Technology (IJSRAT), 5(6), 8953–8956.
33. Chenna, S. (2023). Solution-led integration architecture in Oracle EBS: A dual case study from foundational enterprise engagements. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(1), 8105–8113. https://doi.org/10.15662/IJRPETM.2023.0601010
34. Vankayala, S. C. (2021). Engineering Quality into Cloud-Native Financial Platforms on Microsoft Azure. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 4(1), 4361-4367.
35. Meesala, A. (2022). Adaptive Spread Anomaly Intelligence Framework (ASAIF): A cloud-native AI framework for real-time bid-ask spread anomaly detection and cross-venue liquidity risk intelligence. International Journal of Future Innovative Science and Technology (IJFIST), 5(6), 9597–9604.
36. Yamsani, N. (2019). Engineering trustworthy enterprise data through structured validation and cleansing controls: Insights from Elavon data quality operations. International Journal of Science, Engineering and Technology, 7(1). Zenodo.https://doi.org/10.5281/zenodo.18194337
2. Jayaraman, S., Rajendran, S., & P, S. P. (2019). Fuzzy c-means clustering and elliptic curve cryptography using privacy preserving in cloud. International Journal of Business Intelligence and Data Mining, 15(3), 273-287.
3. Polamreddy, V. R. (2022). Architecting Hybrid Synchronization Models to Enable Safe International Platform Transitions. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 5(1), 6216-6229.
4. Chettiyar, S. S. S. (2023). A vendor-neutral omnichannel conversational payment architecture for conversational commerce integrating BYOP, native solutions, and PCI compliance. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(1), 8124–8135. https://doi.org/10.15662/IJRPETM.2023.0601012
5. Boddupally, H. L. (2021). Quality Forecasting and Reliability Modeling in Expansive. NET Application Landscapes. Available at SSRN 6266042.
6. Tasleem, N., & Gangadharan, S. (2022). Navigating stakeholder dynamics in large-scale transformations. Journal of Advance Multidisciplinary Research, 1(2), 48-56.
7. Goel, N. (2023). Zero Trust Architecture: A Revolutionary Approach to Cybersecurity. Res Militaris, 13(3), 6931-6940.
8. Kanji, M. R. K. (2022). A Unified Data Warehouse Architecture for Multi-Source Forest Inventory Integration and Automated Remote Sensing Analysis. Journal Of Engineering And Computer Sciences, 1(5), 10-16.
9. Veershetty, G. (2019). From Legacy Back Office to Intelligent Utility Enterprise a Practitioner Case Study of SAP Cloud Transformation and Utility IT Landscape Modernization. American International Journal of Computer Science and Technology, 1(1), 23-27.
10. Govindan, V. (2023). AI-powered optimization of non-production environments: Turning constraints into business value. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(1), 8089–8104. https://doi.org/10.15662/IJRPETM.2023.0601009
11. Alex Roney Mathew. (2019). Malware analysis of API calls using FPGA hardware level security. International Journal for Research in Applied Science & Engineering Technology, 7(3), 898–900.
12. Devineni, A. (2022). Proactive incident detection in multi-tenant financial cloud platforms. International Journal of Science, Research and Technology (IJSRAT), 5(4), 8136–8139.
13. Raj, A. A., & Sugumar, R. (2023, June). Early Detection of COVID-19 with Impact on Cardiovascular Complications using CNN Utilising Pre-Processed Chest X-Ray Images. In 2023 International Conference on Applied Intelligence and Sustainable Computing (ICAISC) (pp. 1-6). IEEE.
14. Soundappan, S. J. (2022). Integrated Risk Governance Framework for Financial Compliance Supply Chain Resilience and Enterprise Data Management. International Journal of Computer Technology and Electronics Communication, 5(6), 16254-16263.
15. Syed, S. (2023). A GxP-compliant integrated ERP framework for synchronizing OPM, SCM, and quality lab systems in pharmaceutical manufacturing. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(1), 8064–8076. https://doi.org/10.15662/IJRPETM.2023.0601007
16. Raja, G. V. (2022). Integrating network forensics with data mining for advanced cybercrime investigation. International Journal of Engineering & Extended Technologies Research (IJEETR), 4(5), 5321-5326.
17. Gopisetty, S. (2022). Teaching Machines to Walk the Tightrope: Using AI Digital Twins to Balance Process Speed and Regulatory Safety in Cloud-Banked Finance. Journal of Scientific and Engineering Research, 9(8), 183-226.
18. Mannem, S. (2023). Intelligent service behavior analysis for early cyber threat prediction. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(1), 8077–8088. https://doi.org/10.15662/IJRPETM.2023.0601008
19. Soni, H., & Ramamurthy, P. (2023). Designing modular AI architectures for enterprise scale: From monolithic models to composable AI systems. International Journal of Research Publications in Engineering, Technology and Management, 6(1), 8136–8141.
20. Joyce, S. (2023). Accelerating Enterprise SAP Workload Performance and Automation Using Microsoft Azure Center for SAP Solutions Through Cloud Native Architecture Intelligent Orchestration and Infrastructure as Code. IACSE-International Journal of Information Technology (IACSE-IJIT), 4(1), 8-30.
21. Gummadi, V. P. K. (2020). API design and implementation: RAML and OpenAPI specification. Journal of Electrical Systems, 16(4).
22. Navandar, P. (2023). Ensemble based intrusion detection in heterogeneous networks: A machine learning framework with zero trust integration. International Journal of Advanced Engineering Science and Information Technology, 6(1), 10827–10837. https://doi.org/10.15662/IJAESIT.2023.0601004
23. Raja, G. V., & Mali, R. K. (2022). Building cognitive technology frameworks through artificial intelligence SAP cloud automation and enterprise intelligence. The International Journal of Research Publications in Engineering, Technology and Management, 5(4), 7152–7162.
24. Kotla, Mutha Ravi Tej (2021). Machine learning-based predictive observability for enterprise integration platforms. Journal of Computer Engineering and Technology, 4(3), 1–24. https://doi.org/10.34218/JCET_04_03_001
25. Wadhwa, R. (2023). Designing scalable enterprise systems using event-driven microservices and distributed data architecture for high-throughput business applications. International Journal of Computer Engineering and Technology, 14(3), 323-337.
26. Konakalla, K. (2023). Automating customer feedback collection in Salesforce Service Cloud for enhanced case management and service improvement. Journal of Marketing & Supply Chain Management, 1-3.
27. Siddiqui, M. I. H., Bishnu, K. K., Al Mamun, M. A., Raihan, M., Islam, A., Akter, S., & Hossain, I. (2023). Explainable Federated Deep Learning for Low-Cost and Privacy-Preserving Early Breast Cancer Screening to Reduce US Healthcare Burden. Vascular and Endovascular Review, 6(2), 45-54.
28. Alex Mathew. (2023). Threat defense through cyber fusion. International Journal of Computer Science and Mobile Computing, 12(1), 24–27. https://doi.org/10.47760/ijcsmc.2022.v12i01.003
29. Prasanna Kumar Natta. (2022). Computer-vision-assisted retail inventory automation: Integrating autonomous scan data with worklist completion systems. International Journal of Science, Research and Technology, 5(6), 8957–8969. https://doi.org/10.15662/IJSRAT.2022.0506009
30. Sarngadharan, S. (2023). Federated data pipelines enabling continuous contract and asset state traceability. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(1), 8114–8123. https://doi.org/10.15662/IJRPETM.2023.0601011
31. Gandikota, S. P. (2023). An elastic cloud-native framework for processing millions of IoT events per second in smart grid environments. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(1), 8049–8063. https://doi.org/10.15662/IJRPETM.2023.0601006
32. Mohammed, S. (2022). Designing secure zero trust architectures for global enterprise environments. International Journal of Science, Research and Technology (IJSRAT), 5(6), 8953–8956.
33. Chenna, S. (2023). Solution-led integration architecture in Oracle EBS: A dual case study from foundational enterprise engagements. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(1), 8105–8113. https://doi.org/10.15662/IJRPETM.2023.0601010
34. Vankayala, S. C. (2021). Engineering Quality into Cloud-Native Financial Platforms on Microsoft Azure. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 4(1), 4361-4367.
35. Meesala, A. (2022). Adaptive Spread Anomaly Intelligence Framework (ASAIF): A cloud-native AI framework for real-time bid-ask spread anomaly detection and cross-venue liquidity risk intelligence. International Journal of Future Innovative Science and Technology (IJFIST), 5(6), 9597–9604.
36. Yamsani, N. (2019). Engineering trustworthy enterprise data through structured validation and cleansing controls: Insights from Elavon data quality operations. International Journal of Science, Engineering and Technology, 7(1). Zenodo.https://doi.org/10.5281/zenodo.18194337
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