Comparing Zero Trust Model with Traditional Network and Machine Learning Enhancement in OpenZITI

Joshy, Elsamma (2024) Comparing Zero Trust Model with Traditional Network and Machine Learning Enhancement in OpenZITI. Masters thesis, Dublin, National College of Ireland.

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Abstract

Cybersecurity threats are evolving. This makes protecting sensitive information complicated when accessing it remotely. Traditional VPNs, despite their efficiency in encrypting data, can protect against advanced insider threats and identity theft. Due to its boundary- and static design, Zero Trust Network Architecture (ZTNA), which leverages the “never trust, always verify” principle, provides a dynamic security framework. This study compares the performance and security of OpenVPN (VPN) and OpenZiti (ZTNA) using latency, throughput, jitter and other measures. Additionally, machine learning (ML) models (random forest, logistic regression, XGBOOST) analyze the datasets. UNSW-NB15 to detect infiltration. The results indicate that ZTNA outperforms VPN in terms of delay and jitter. This reduces access and the restricted attack surface. ML enhancements further improve threat detection compared to ZTNA VPN. This functionality helps enterprises move to a modern security framework.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Moldovan, Arghir Nicolae UNSPECIFIED
Uncontrolled Keywords:	OpenZiti; OpenVPN; Zero-Trust Network (ZTN); Virtual Private Network (VPN); Machine Learning (ML); Throughput; Jitter; Random Forest Classifier; Logistic Regression
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:	23 Jul 2025 14:05
Last Modified:	23 Jul 2025 14:05
URI:	https://norma.ncirl.ie/id/eprint/8216

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