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@article{206838,
        author = {Shashank Naik and Chaitra Kedaliya and Naman S and Kartik and Sujay},
        title = {Phishing Link Detection Using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {no},
        pages = {642-645},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=206838},
        abstract = {Phishing threats continue to pose a challenge and are among the greatest threats to internet users due to their exploitation by use of phishing URLs. The paper suggests an algorithmic way of detecting phishing links that takes into account the scalability of today's research approaches. The algorithm is based on heuristics and scalable learning technology which ensures real-time phishing detection at a minimum computational cost. The system employs lexical, structural, and domain-based features to effectively classify URLs. Phishing threats continue to pose a challenge and are among the greatest threats to internet users due to their exploitation by use of phishing URLs. The paper suggests an algorithmic way of detecting phishing links that takes into account the scalability of today's research approaches. The algorithm is based on heuristics and scalable learning technology which ensures real-time phishing detection at a minimum computational cost. The system employs lexical, structural, and domain-based features to effectively classify URLs},
        keywords = {.},
        month = {July},
        }