Venkatesh Babu, Deepak (2025) EZTSM: Enhanced Zero Trust Security Model for Serverless Computing with ML based Anomaly Detection. Masters thesis, Dublin, National College of Ireland.
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Abstract
Enhanced Zero Trust Security Model (EZTSM) specifically designed for serverless computing is the proposed solution, that combines machine learning based anomaly detection using the Isolation Forest algorithm and Zero Trust Security framework along with real-time monitoring. The traditional perimeter-based security models are not sufficient to protect the modern cloud-native architectures due to its limitations such as static role-based access control, particularly serverless platforms that operates on dynamic, event-driven functions. This study addresses these limitations by designing, developing, implementing and evaluating a scalable and performance-oriented security framework for serverless on AWS cloud. While the existing Zero Trust framework remains theoretical and lacks proven evidence. This research also evaluates EZTSM with serverless computing, focusing on latency, throughput, anomaly detection accuracy, scalability, and response to simulated attacks. The model is built using AWS-native services enables easy setup and implementation. The results show how EZTSM can enhance security posture while maintaining acceptable performance trade-offs in dynamic cloud environments.
| Item Type: | Thesis (Masters) |
|---|---|
| Supervisors: | Name Email Kazmi, Aqeel UNSPECIFIED |
| Subjects: | T Technology > T Technology (General) > Information Technology > Cloud computing Q Science > QA Mathematics > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning |
| Divisions: | School of Computing > Master of Science in Cloud Computing |
| Depositing User: | Ciara O'Brien |
| Date Deposited: | 31 Mar 2026 12:21 |
| Last Modified: | 31 Mar 2026 12:21 |
| URI: | https://norma.ncirl.ie/id/eprint/9276 |
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