Leveraging Intrusion Detection System: Based on Fog-to-Cloud Computing

Umrikar, Mayuri Ganesh (2024) Leveraging Intrusion Detection System: Based on Fog-to-Cloud Computing. Masters thesis, Dublin, National College of Ireland.

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Abstract

This paper outlines a rule-based Intrusion Detection System designed and deployed on a Fog-to-Cloud computing architecture for network security enhancement. It uses the UNSW-NB15 dataset to classify the network traffic as either benign or malicious based on the predefined heuristics. Analysis of source and destination byte counts, protocol type, and duration are considered in order to detect the threats like data exfiltration, ping floods, and worm attacks. The IDS is implemented as a serverless application through AWS Lambda, which allows the cost-efficient, scalable, and real-time processing of network data. AWS API Gateway simplifies interaction with external systems by providing a REST API endpoint for processing traffic data. There were some issues with CORS since API Gateway and Lambda are configured to handle preflight requests with proper headers. This system acts as a base for implementing the principles of Fog-to-Cloud computing where data is preprocessed at the local level at the fog nodes before the critical insights are forwarded to the cloud for further analysis. The project proves the feasibility of intrusion detection through serverless architecture as it is lightweight, flexible, and scalable. The next step is the integration of machine learning models to provide improved accuracy and live monitoring of streams of traffic in real-time against the evolving cyber threats.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Heeney, Sean UNSPECIFIED
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
Divisions:	School of Computing > Master of Science in Cloud Computing
Depositing User:	Ciara O'Brien
Date Deposited:	17 Jul 2025 12:44
Last Modified:	17 Jul 2025 12:44
URI:	https://norma.ncirl.ie/id/eprint/8161

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