Raut, Piyush Rajkumar (2024) An intelligent Docker container-based solution with multiple IDS to filter DoS attack. Masters thesis, Dublin, National College of Ireland.
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Abstract
This research focuses on enhancing the security of Docker container environments against denial-of-service (DoS) attacks through the deployment of multiple open-source Intrusion Detection Systems (IDS) tools. Docker containers are vulnerable to various DoS attacks that can severely impact system performance. This study integrates Snort, Suricata, and Zeek IDS tools within a Dockerized setup, using the ELK Stack for centralized log management and real time monitoring. The methodology involves simulating different types of DoS attacks, such as ICMP, TCP SYN, and UDP flood attacks to evaluate the detection capabilities of each IDS tool. The results demonstrate that a multi-layered defense strategy, combining the strengths of each tool significantly improves detection accuracy, scalability, and system efficiency. Snort was best in real time detection, Suricata managed high traffic volumes efficiently and Zeek provided in depth network analysis, making them a solution for securing Docker environments. The solution enhanced scalability and efficiency for DoS detection by using these tools together. Future work includes the integration of machine learning techniques to further enhance detection capabilities.
Item Type: | Thesis (Masters) |
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Supervisors: | Name Email Mahajan, Kamil UNSPECIFIED |
Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science 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 Cyber Security |
Depositing User: | Ciara O'Brien |
Date Deposited: | 31 Jul 2025 08:12 |
Last Modified: | 31 Jul 2025 08:12 |
URI: | https://norma.ncirl.ie/id/eprint/8360 |
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