An Active Defense Security Framework using Deep Reinforcement Learning for Container-Based Architectures

Avula, Mahesh Kumar (2024) An Active Defense Security Framework using Deep Reinforcement Learning for Container-Based Architectures. Masters thesis, Dublin, National College of Ireland.

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Abstract

In this research, we present an active defense security framework for the container environments for overcoming the dynamic security challenges of containerized applications. We employ deep reinforcement learning (DRL) to optimize adaptive threat response and resource utilization within the framework. It presents a dynamic Holistic System Attack Graph (HSAG) model of time varying behavioral analysis of container activities, along with a novel Prioritized Dueling Double Deep Q Network (P3DQN) for security optimization at its foundation. A comprehensive security evaluation system is designed in the framework that is capable of real time monitoring, analysis and automatic response. Detection rates reported are 98.5% for CPU attacks and 96.8% for memory incident with 0.8% false positive rate. During normal operation, average CPU usage never exceeded 3.19%, and peak usage during active incident response was 25.04%. For detected incidents, the framework achieved an average of 17.42 seconds from detection to completion of the action (17.42s onset to action complete with a prevention rate of 100 per cent. This shows the effectiveness of the framework to provide real time security monitoring and response with optimal resource utilization in containerized service environments.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Heeney, Sean UNSPECIFIED
Uncontrolled Keywords:	Container Security; Deep Reinforcement Learning; HSAG; Cloud Computing
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science 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:	14 Jul 2025 14:27
Last Modified:	14 Jul 2025 14:27
URI:	https://norma.ncirl.ie/id/eprint/8083

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