E-MAIL SPAM DETECTION

E-MAIL SPAM DETECTION

Jayashree Lavhare1, Shreya Kosabe2, Pooja Kolge3,Pranita Wagh4,Akshay Ghuge5

1Jayashree Lavhare Information Technology Department & P .G. Moze College of Engineering

2Shreya Kosabe Information Technology Department & P.G.Moze College of Engineering

3Pooja Kolge   Information Technology Department & P.G.Moze College of Engineering

4Pranita Wagh   Information Technology Department & P.G.Moze College of Engineering

5Akshay Ghuge Information  Technology Department & P.G.Moze College of Engineering

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Abstract - Emails have become a ubiquitous means of personal and professional communication, often containing sensitive and confidential information. However, they are also prime targets for cybercriminals who employ techniques such as phishing to obtain private data. This paper proposes an intelligent and efficient email spam detection system that leverages data mining algorithms for classification and association. By extracting multiple features from email content, we improve classification accuracy and efficiency. The system integrates various machine learning algorithms and achieves a 30% reduction in the error rate compared to existing methods. Our approach enhances email spam detection by combining support vector machines with multi-feature extraction and classification.

Key Words:  Support vector machines, Email Spam, Phishing Detection, Machine Learning, Multi-Feature Extraction.