Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM66937
Volume:
10 |
8 |
Aug 2026
Pages:
1-12
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.
School of Sciences (BCA)
KK Modi University Durg
School of Sciences (BCA)
KK Modi University Durg
The paradigm shift toward serverless computing, predominantly actualized through the Function-as-a-Service (FaaS) model, has redefined cloud resource provisioning by abstracting infrastructure management and introducing auto-scaling, pay-as-you-go financial paradigms. While this architecture offers unparalleled computational elasticity and operational simplicity, it simultaneously broadens the attack surface, rendering applications uniquely vulnerable to asymmetric threats. Foremost among these are Denial of Wallet (DoW) attacks, control-flow hijacking within ephemeral sandboxes, and emerging vulnerabilities targeting serverless Artificial Intelligence (AI) and Machine Learning (ML) workloads. Conventional perimeter-based security mechanisms fail to accommodate the rapid execution lifecycle, the phenomenon of dead-provenance, and the economic exploitation models inherent to FaaS platforms. This research proposes a robust, multi-layered security framework designed to proactively detect, mitigate, and conduct forensic analysis on distributed serverless intrusions. By synthesizing pre-deployment validation, runtime Control-Flow Integrity (CFI), Moving Target Defense (MTD) coupled with N-Version Programming (NVP), deep learning-driven anomaly detection, and global provenance reconstruction, the proposed architecture provides deterministic protection against diverse threat vectors. Experimental validation utilizing a Kubernetes and Knative-based simulation environment demonstrates that the integrated framework successfully neutralizes Blast and Continual Inconspicuous DoW attacks, blocks control-flow manipulations, and mitigates AI-specific vulnerabilities such as model extraction and adversarial poisoning. The framework achieves a 96.8% aggregate threat detection rate while imposing a manageable execution latency overhead of 14.2%, establishing the operational viability of combining deep introspection with cost-aware security enforcement in highly distributed microservice ecosystems.
KEYWORDS
The transition toward serverless computing provides dramatic operational benefits but introduces novel attack surfaces defined by ephemeral execution, distributed coordination, and cost-based auto-scaling. Legacy security postures are structurally incapable of defending against highly specific, cloud-native threats such as Denial of Wallet, warm-container control-flow hijacking, and adversarial AI poisoning. The comprehensive architecture proposed in this research establishes a resilient, multi-tiered defense tailored explicitly for the constraints and mechanics of Function-as-a-Service environments. By combining automated N-Variant generation with runtime CFI enforcement and TLS offloading, the system effectively isolates and neutralizes code execution vulnerabilities. The application of NVP and MTD disrupts deterministic exploit chains, preventing lateral movement across microservices. Furthermore, the integration of deep learning anomaly detection successfully neutralizes stealthy financial exhaustion campaigns, while global provenance graphing enables high-fidelity post-incident forensic analysis despite the rapid termination of containers. Extensive empirical simulations prove that the architecture can yield a 96.8% aggregate interception rate for critical threats with a manageable average latency penalty of 14.2%. Ultimately, securing the serverless paradigm requires acknowledging its unique economic and architectural properties and implementing deeply integrated, cost-aware security enforcement mechanisms.
[1] P. Datta, I. Polinsky, M. A. Inam, A. Bates, and W. Enck, "ALASTOR: Reconstructing the provenance of serverless intrusions," in Proceedings of the USENIX Security Symposium, 2022. [2] D. S. Jegan, L. Wang, S. Bhagat, and M. Swift, "Guarding serverless applications with Kalium," in Proceedings of the USENIX Security Symposium, 2023. [3] K. Alpernas et al., "Secure serverless computing using dynamic information flow control," in Proceedings of the ACM on Programming Languages, 2018. [4] P. Escaleira, V. A. Cunha, J. P. Barraca, D. Gomes, and R. L. Aguiar, "Enhancing Serverless Function Resilience Against Vulnerabilities with MoFaaS," Journal of Network and Systems Management, 2026. [5] D. Kelly, F. Glavin, and E. Barrett, "DoWNet - classification of Denial-of-Wallet attacks on serverless architectures," Journal of Cybersecurity, 2024. [6] Pathade, Lavi, et al., "Serverless AI Security & Compromised Functions." [7] Li et al., "The Serverless Computing Survey: A Technical Primer." [8] M. Xiong, Z. Lu, and Y. Liu, "Warmonger: inflicting denial-of-service via serverless functions in the cloud," in Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security, 2021. [9] A. S. Cassel et al., "Serverless computing for Internet of Things: A systematic literature review," Future Generation Computer Systems, 2022. [10] Y. Li et al., "Serverless computing: state-of-the-art, challenges and opportunities," IEEE Transactions on Services Computing, 2022.
Publication Date
8/25/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
0
Total views since publication
PDF Downloads
3
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...