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@article{175441,
        author = {Nikita Gujarkar and Nitin Shelokar and Nikita Tamkhane and Nikita Amale and Divyani Gayakwad and Ruchika Rahate},
        title = {Detection Phishing Website Using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {2792-2798},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175441},
        abstract = {The net has up to date a breeding floor for cyber threats, including malicious internet pages and assaults. Researchers have been operating tirelessly updated increase effective strategies for detecting and mitigating these threats. Patil and colleagues conducted a thorough research inupdated existing strategies for figuring out malicious web pages, highlighting the diverse present-day attacks and introducing features and algorithms for detection. Their research emphasizes the significance up-to-date dynamic up-to-date management structures and the need for progressive methods up-to- date correctly classify and locate malicious URLs in actual-time. while progress has been made, ongoing studies is important up-to-date stay in advance modern emerging threats and ensure sturdy cybersecurity measures.},
        keywords = {},
        month = {April},
        }