Implementing Adaptive Rate Limiting and Honeytokens for Enhanced REST API Security in JavaScript Web Applications

Nwobbi, Chinelo Lauren (2025) Implementing Adaptive Rate Limiting and Honeytokens for Enhanced REST API Security in JavaScript Web Applications. Masters thesis, Dublin, National College of Ireland.

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Abstract

Application Programming Interfaces used for transmitting information remain vulnerable to various attack vectors. Current mitigation strategies involve employing API best practices such as static rate limiting, encryption and input validation, using machine learning algorithms to detect API misuse and other security frameworks. While these strategies support security, issues like computational complexity, costs and inflexibility hinder progress and security effectiveness. This paper analyses adaptive rate limiting and honeytoken mechanisms as a tool to enhance REST API security by proposing a model that integrates these mechanisms, analysing request behaviour when handling traffic. The proposed model obtained an accuracy rate of 86.36% when detecting bots and effectively applied rate limiting for identified bot and human threat actor traffic. This paper will support developers when building REST APIs with a ready tool for enhancing rate-limiting capabilities and strengthening API endpoints.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Hafeez, Khadija 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:	16 Jun 2026 13:52
Last Modified:	16 Jun 2026 13:52
URI:	https://norma.ncirl.ie/id/eprint/9365

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