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A Comprehensive Model for Spam Detection and Phishing Link Detection

Author

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  • Shilpi Jain
  • Madhur Jain
  • Ridhi Kalia
  • Divyansh Rampal

Abstract

The rapid evolution of technology in recent decades has brought about unprecedented connectivity, efficiency gains, and innovations across various sectors. However, this digital advancement has given rise to new and complex challenges, particularly cybersecurity. This paper presents our project for detecting spam messages/content and phishing links using machine learning algorithms. By comparing various algorithms, we aim to accurately identify and classify suspicious websites and content to mitigate malicious attempts. Our methodology involves training the model on a comprehensive dataset comprising known instances of phishing websites and spam content. Subsequently, the model is employed to classify new websites and content based on their distinct features and characteristics. We exhibit the efficacy of our method by comprehensive testing and assessment on an actual dataset.

Suggested Citation

  • Shilpi Jain & Madhur Jain & Ridhi Kalia & Divyansh Rampal, 2024. "A Comprehensive Model for Spam Detection and Phishing Link Detection," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 10(3), pages 349-353, June.
    • Handle: RePEc:jbh:ijsrcs:v10:y2024:i3:id:210
    DOI: 10.32628/CSEIT24103109
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT24103109
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