Study of SPAM Email Detection
G.Mohan Sai Krishna1
*,
K.Eswar Teja, D.Harshavardhan Reddy
- 1Anna University Chennai, Department of Computer Science and Engineering, Prathyusha Engineering College, Tiruvallur, Chennai- 602025, IN
A Many businesses and people now have easier ways to communicate thanks to electronic mail. Spammers who send unwanted emails use this technique to their advantage in order to make false gains. With machine learning algorithms that are enhanced using bio-inspired techniques, the goal of this paper is to show a method for spam email detection. A literature review is conducted to investigate the effective techniques used on various datasets to produce excellent results. On seven distinct email datasets, extensive research was conducted to apply machine learning models using Naive Bayes, Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, and Multi-Layer Perceptron, along with feature extraction and pre-processing. To enhance the effectiveness of classifications, algorithms were put into place. Overall, the greatest performance was shown by logistic regression. Our findings are compared to those of other machine learning models in order to determine which model is the most appropriate.
Conclusion
Email has been the most important medium of communication nowadays; through internet connectivity any message can be delivered to all over the world. More than 270 billion emails are exchanged daily, about 57% of these are just spam emails. Spam emails, also known as non-self, are undesired commercial or malicious emails, which affects or hacks personal information like bank, related to money or anything that causes destruction to single individual or a corporation or a group of people. Besides advertising, these may contain links to phishing or malware hosting websites set up to steal confidential information. Spam is a serious issue that is not just annoying to the end-users but also financially damaging and a security risk. Hence this system is designed in such a way that it detects unsolicited and unwanted emails and prevents them hence helping in reducing the spam message which would be of great benefit to individuals as well as to the company .In the future this system can be implemented by using different algorithms and also more features can be added to the existing system.
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Keywords: spam, email detection, machine learning
Citation: G.Mohan Sai Krishna*, G.Mohan Sai Krishna ( 2023), Study of SPAM Email Detection. , 11(2): 1-4
Received: 17/06/2024; Accepted: 17/06/2024;
Published: 17/06/2024
Edited by:
Mr.ERES JOURNALSReviewed by:
Copyright: @ERES Publications.
*Correspondence: G.Mohan Sai Krishna, mohansaikrishnagundluru@gmail.com
