Evaluating the Effectiveness of Multi Factor Authentication

Patel, Deep Rakeshbhai (2024) Evaluating the Effectiveness of Multi Factor Authentication. Masters thesis, Dublin, National College of Ireland.

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Abstract

This research presents an integrated approach to early detection and prevention of Distributed Denial-of-Service (DDoS) attacks using ensemble machine learning techniques combined with One-Time Password (OTP) authentication. The study implements a web application that utilizes Random Forest, Decision Tree, and Support Vector Machine (SVM) models trained on the NSL-KDD dataset. The Random Forest model demonstrated superior performance with 96.1% accuracy in detecting various attack types, particularly excelling in identifying DoS (98.3%) and Probe (93.3%) attacks. The system incorporates OTP-based email verification, achieving a 6.2-second average response time and 90% first-attempt verification success rate. Real-time testing showed the application maintained 97.5% prediction accuracy with a 1.3-second average response time. While the solution effectively handles common attack patterns, challenges remain in detecting R2L and U2R attacks due to dataset imbalances. The research contributes to cybersecurity by combining robust attack detection with secure access control mechanisms.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Pantridge, Michael 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:	28 Jul 2025 08:54
Last Modified:	28 Jul 2025 08:54
URI:	https://norma.ncirl.ie/id/eprint/8240

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