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@article{199072,
        author = {Snehil Hemant Suryawanshi and Madhura Pramod Pawar and Prajakta Vishwas Bhosale and Ananya Pandey and Dr.Vanitha Soman},
        title = {SpamGuard: Spam Email Detection Extension},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {15214-15217},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=199072},
        abstract = {SpamGuard is a browser-based email security extension designed to detect and filter spam emails in real-time using machine learning techniques. With the rapid growth of phishing attacks and malicious email content, there is a need for intelligent and adaptive spam detection systems. SpamGuard utilizes Natural Language Processing (NLP) and classification algorithms to analyze email content, sender behavior, and embedded links. The system provides real-time alerts and categorization, improving both security and user productivity. Experimental results demonstrate high accuracy and reduced false positives, making SpamGuard a reliable and efficient solution for modern email security challenges.},
        keywords = {Spam Detection, Email Security, Machine Learning, NLP, Phishing, Browser Extension, Cybersecurity},
        month = {April},
        }