The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Enhancing Threat Detection and Response Through Cloud-Native Security Solutions
Abstract
In a dynamic cyber environment, the automation of threat detection and response has become critical in safeguarding sensitive information. The complexity and scale of traditional security systems make them inadequate to handle the modern cyber threats. Cloud-native security solutions, integrated into machine learning and artificial intelligence, provide an effective, scalable, and automated way to detect and mitigate security threats in real time. Such solutions exploit the natively scalable, flexible, and resilient nature of cloud infrastructures. This paper deliberates on the contribution of cloud-native security tools towards the automation of threat detection and response. Based on architecture, functionality, and effectiveness of such solutions, we analyze their case studies emanating from top-notched cloud providers. In such case studies, we explained how real-time data analysis is leveraged to automatically discover potential threats like zero-day attacks and insider threats. Our study also includes performance results based on cloud-native architectures, presented in the way they minimize human intervention and speed up responses. Automating the process made it possible for businesses to pay more attention to proactive security measures and thereby mitigate possible breaches with more ease. In conclusion, a cloud-native security automation transforms the entire way that enterprises protect their assets against threats. It provides a risk-proofed solution for the future, reassuring people of safety from new and emerging risks.
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“For example, refs.[20,48,49] explore innovative techniques for scaling threat detection in decentralized architectures, reflecting a shift toward real-world deployment in complex infrastructures.”
From Application of Machine Learning and Deep Learning Techniques for Enhanced Insider Threat Detection in Cybersecurity: Bibliometric Review (2025) · cites this paper as [20]
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Cites
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Secure Cloud Infrastructure: A Survey on Issues, Current Solutions, and Open Challenges
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Toward Supporting XR Services: Architecture and Enablers
Taleb, T., Boudi, A., Rosa, L., Cordeiro, L., Θεοδωρόπουλος, Θ., Tserpes, K., Dazzi, P., Protopsaltis, A. I., & Li, R. Z. (2022) · IEEE Internet of Things Journal · doi:10.1109/jiot.2022.3222103 · Cited by 66
AI-Based Autonomic and Scalable Security Management Architecture for Secure Network Slicing in B5G
Benzaïd, C., Taleb, T., & Song, J. (2022) · IEEE Network · doi:10.1109/mnet.104.2100495 · Cited by 55
A Survey on Resource Management for Cloud Native Mobile Computing: Opportunities and Challenges
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Performance Impact of Microservices Architecture
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Ofori, H. K., Bell-Dzide, K., Brown-Acquaye, W. L., Lempogo, F., Frimpong, S. O., Agbehadji, I. E., & Millham, R. C. (2025) · Symmetry · doi:10.3390/sym17101704 · Cited by 7
Alagesan, M., Kachana, K. R., & AKKURT, B. H. (2025) · International Journal of Computational and Experimental Science and Engineering · doi:10.22399/ijcesen.4203
Artificial Intelligence in Financial Cybersecurity: A Comprehensive Review
Worapaluk, K., Wongvises, C., Lapmoon, J., Chanyavilas, N., & Luangingkasut, C. (2026) · International Conference on Knowledge and Smart Technology · doi:10.1109/kst67832.2026.11432364
Metadata
- Authors
- Kumar, S., & Raju, S.
- Affiliations
- SME in Cloud Engineering,Georgia,USA
- ORCID
- Kumar, Sanjeev
- Venue
- 2024 International Conference on Engineering and Emerging Technologies (ICEET)
- Publisher
- IEEE
- Published
- 2024-12-27
- Pages
- 1-6
- OpenAlex
- W4408358308
- Cited by
- 3
- References
- 13
- Citations by year
- 2026: 1 · 2025: 2
- FWCI
- 1.31
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Engineering and Emerging Technologies (ICEET) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Physical Sciences › Computer Science › Information Systems › Cloud Data Security Solutions
- Physical Sciences › Computer Science › Computer Networks and Communications › Cybersecurity and Information Systems
- Keywords
- cloud-native security, threat detection, zero-day attacks, insider threats, machine learning for cybersecurity, artificial intelligence for security
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