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@article{194710,
        author = {Ms. Samruddhi Bajpayee and Mr. Aditya Talwatkar and Mr. Vivek Jadhao and Ms. Aarya Thakare and Mr. Yash Pali and Prof. Dipali Sananse},
        title = {PhishGuard: An Intelligent Browser Extension for Real-Time Phishing Website Detection Using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {5134-5139},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=194710},
        abstract = {Phishing websites pose a significant threat to online security by tricking users into revealing sensitive information such as login credentials and financial data. Traditional blacklist-based detection methods are often ineffective against newly created phishing websites. This paper proposes PhishGuard, a real-time phishing website detection system that integrates machine learning with a browser extension. The system extracts URL-based features and uses a trained machine learning model to classify websites as phishing or legitimate. The browser extension continuously monitors visited websites and alerts users when a suspicious site is detected, providing enhanced protection against phishing attacks during web browsing.},
        keywords = {Phishing Detection, Machine Learning, PhishGuard, Browser Extension, Real-Time Detection.},
        month = {March},
        }