Implementation of Cyrillic Script Checker to Detect Phishing Attacks URLs/links

Gupta, Suraj Rakesh (2025) Implementation of Cyrillic Script Checker to Detect Phishing Attacks URLs/links. Masters thesis, Dublin, National College of Ireland.

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Abstract

This study outlines the challenges faced and creation of Cyrillic Script Checker that aimed at identifying homograph attacks that exploit visual resemblances between Cyrillic and Latin letters. The system tackles an important security issue where attackers replace visually similar Cyrillic characters, like the Cyrillic 'а' (U+0430) in place of the Latin 'a' (U+0061), forming misleading URLs such as fаcebook.com that seem authentic yet lead users to harmful sites. The solution in place utilizes a client-side web application structure that incorporates HTML5, CSS3, and JavaScript to enable real-time analysis of Unicode characters in the Cyrillic Unicode range (U+0400 to U+04FF). The identification system employs regular expression pattern matching to recognize Cyrillic characters in URLs, providing instant classification with no computational expense. The system includes an educational feature via a homograph generator that illustrates typical Latin-Cyrillic character replacements, increasing user understanding of the threat environment. Test scenarios attained flawless performance indicators with 100% detection accuracy, no false positives, and no false negatives throughout 102 URL and I have mentioned Ten test examples involving authentic domains (google.com, x.com, instagram.com) and their related Cyrillic homograph counterparts. The client-side framework protects user privacy by avoiding server-side data transfer while preserving real-time threat detection functionality. This study offers a lightweight, deterministic detection method aimed specifically at populations within the Cyrillic Orthographic Zone (Belarus, Bulgaria, Russia, and Ukraine), tackling cultural gaps present in current English-focused cybersecurity systems [2][5]. The research shows the efficacy of script-specific detection methods and lays the groundwork for culturally aware cybersecurity solutions that can adjust to region-specific threat and language features.

Item Type:	Thesis (Masters)
Supervisors:	Name Email McLaughlin, Eugene UNSPECIFIED
Uncontrolled Keywords:	Homograph attacks; Cyrillic script detection; Unicode-based phishing; Client-side cybersecurity; Cross-cultural threat detection
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
Divisions:	School of Computing > Master of Science in Cyber Security
Depositing User:	Ciara O'Brien
Date Deposited:	17 Aug 2026 14:41
Last Modified:	17 Aug 2026 14:41
URI:	https://norma.ncirl.ie/id/eprint/9531

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