A Next-Generation Zero-Trust Security Framework for Cloud-Native Microservices Powered by AI

DOI

10.2991/978-94-6239-664-7_63How to use a DOI?

Keywords

Zero-Trust Security; Cloud-Native Microservices; Artificial Intelligence; Intrusion Detection; Continuous Authentication

Abstract

Static zero-trust policies frequently fall short of offering adequate defense against changing threats in cloud-native microservices’ highly dynamic and distributed environments. An AI-powered zero-trust security framework that incorporates real-time anomaly detection straight into the policy-enforcement loop is presented in this paper. The framework continuously monitors interservice communication, uses a hybrid model that combines supervised and unsupervised techniques to generate anomaly scores, and modifies least-privilege rules in response to changes in traffic conditions. We set up the system in a Kubernetes testbed and used common intrusion datasets to train the models in order to assess the method. According to experimental findings, the framework maintains acceptable latency and resource overhead for microservice operations while increasing detection accuracy and decreasing false positives when compared to a static rule-based baseline. The results indicate that combining lightweight AI models with zero-trust enforcement can provide a more flexible and useful defense for cloud-native architectures, even though the intrusion datasets introduce some limitations in terms of generalization. More sophisticated learning techniques, larger datasets, and more thorough mitigation workflows are possible future additions.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Mojaidul Islam Asik Chy
AU  - Ridowan Arifin Ridu
PY  - 2026
DA  - 2026/06/08
TI  - A Next-Generation Zero-Trust Security Framework for Cloud-Native Microservices Powered by AI
BT  - Proceedings of the International Conference on Intelligent Data Analysis and Applications (IDAA 2025)
PB  - Atlantis Press
SP  - 919
EP  - 931
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-664-7_63
DO  - 10.2991/978-94-6239-664-7_63
ID  - Chy2026
ER  -