AI-Based Detection and Mitigation of Malware and Phishing Attacks in Malayalam Language Cyber Threats
Abstract: The increasing adoption of regional languages in digital communication has introduced new cybersecurity challenges. In India, cyber attackers are increasingly leveraging Malayalam-language content to conduct phishing and malware-based attacks. Existing detection systems are predominantly designed for English and fail to effectively analyze low-resource languages. This paper proposes an Artificial Intelligence (AI)-based framework for detecting and mitigating Malayalam-language cyber threats. The framework integrates Natural Language Processing (NLP), deep learning models, and transformer-based architectures to analyze linguistic patterns, code-mixed text, and embedded malicious URLs. A curated dataset comprising real and synthetically generated Malayalam messages is used for evaluation. Experimental results indicate that transformer-based models significantly outperform traditional machine learning approaches, achieving high accuracy and reduced false positive rates. The study highlights the necessity of language-aware cybersecurity mechanisms for regional digital ecosystems.
Keywords: Cybersecurity, Malayalam Language, Phishing Detection, Malware Detection, NLP, Transformer Models
How to Cite?: Neetha B.S, "AI-Based Detection and Mitigation of Malware and Phishing Attacks in Malayalam Language Cyber Threats", Volume 15 Issue 3, March 2026, International Journal of Science and Research (IJSR), Pages: 1707-1708, https://www.ijsr.net/getabstract.php?paperid=SR26328212350, DOI: https://dx.doi.org/10.21275/SR26328212350