International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 7, Issue 3 (May-June 2025) Submit your research before last 3 days of June to publish your research paper in the issue of May-June.

Smart Spam Detection: An AI-Based Machine Learning

Author(s) Ms. Prithika S, Prof. Janakiraman S
Country India
Abstract Email has become an essential communication tool, seamlessly facilitating information exchange across personal and professional spheres. While its convenience and global accessibility are unparalleled, email systems have increasingly become targets for cybercriminals exploiting sophisticated spam tactics to breach government networks, corporate systems, and individual accounts. These threats are characterized by their complexity and scale, outpacing traditional detection mechanisms and emphasizing the need for innovative and adaptive solutions to combat emerging cyber risks effectively. This project proposes an advanced system for classifying large-scale email datasets into four distinct categories: Normal, Fraudulent, Harassment, and Suspicious. The approach integrates Natural Language Processing (NLP) with Bidirectional Long Short-Term Memory (BiLSTM) networks to capture nuanced patterns and semantic meanings within email content. The methodology includes a sample expansion phase to enhance training data diversity and a robust testing stage to ensure high accuracy under varied conditions. This innovative system enables effective forensic analysis by extracting and analysing meaningful information from email communications. Through extensive experimentation, the proposed system demonstrates a significant improvement over existing machine learning techniques, achieving a remarkable classification accuracy of 99.1%. The use of BiLSTM with recurrent gradient units ensures reliable performance across diverse email topics and complex scenarios. By offering a highly accurate and robust solution, this project contributes to advancing email security and strengthens the defence mechanisms against evolving cyber threats in today's interconnected digital environment.
Keywords Natural Language Processing(NLP),Supervised Learning,Spam Classification,Feature Extraction,Text Preprocessing
Field Computer Applications
Published In Volume 7, Issue 3, May-June 2025
Published On 2025-06-08
DOI https://doi.org/10.36948/ijfmr.2025.v07i03.47338
Short DOI https://doi.org/g9pz3n

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