The Spam Email Filter Based on the Bayes Method

Authors

  • Zihao Zhou

DOI:

https://doi.org/10.54097/03xmee88

Keywords:

Bayesian; Datasets; Spam email; Filter.

Abstract

There are many spammers send a large amount of spam information to the public. The situation that spammers send spam email is common. The research from AA science have asked 55852 people, all of them claimed that spam email is becoming one part of their live. Nowadays they become used to open their mailboxes and delete the spam email. To deal with this situation people provide some filters to help people indicate which is spam email. Bayes method is one of earliest method, and up to now it still has its importance. This paper introduces the Bayes method, about the Bayesian theory and how it works in the filter to deal with the spam email. And then to analyze the outcomes, about the data and its accuracy. In this paper there also includes some small details that should be mentioned and the advantages and disadvantages of the method.

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References

[1] Agarwal K, Kumar T. Email spam detection using integrated approach of Naïve Bayes and particle swarm optimization. Second International Conference on Intelligent Computing and Control Systems (ICICCS). IEEE, 2018: 685-690.

[2] Zhou B, Yao Y, Luo J. A three-way decision approach to email spam filtering. Advances in Artificial Intelligence: 23rd Canadian Conference on Artificial Intelligence, Canadian AI 2010, Ottawa, Canada, May 31–June 2, 2010. Proceedings 23. Springer Berlin Heidelberg, 2010: 28-39.

[3] Sharabov M, Tsochev G, Gancheva V, et al. Filtering and Detection of Real-Time Spam Mail Based on a Bayesian Approach in University Networks. Electronics, 2024, 13(2): 374.

[4] Rathod S B, Pattewar T M. Content based spam detection in email using Bayesian classifier. International Conference on Communications and Signal Processing (ICCSP). IEEE, 2015: 1257-1261.

[5] Abu-Nimeh S, Nappa D, Wang X, et al. Bayesian additive regression trees-based spam detection for enhanced email privacy. Third International Conference on Availability, Reliability and Security. IEEE, 2008: 1044-1051.

[6] Eberhardt J J. Bayesian spam detection. Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal, 2015, 2(1): 2.

[7] Androutsopoulos I, Koutsias J, Chandrinos K V, et al. An experimental comparison of naive Bayesian and keyword-based anti-spam filtering with personal e-mail messages. Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval. 2000: 160-167.

[8] Ebadati O M E, Ahmadzadeh F. Classification spam email with elimination of unsuitable features with hybrid of GA-naive Bayes. Journal of Information & Knowledge Management, 2019, 18(01): 1950008.

[9] Glickman M E, Van Dyk D A. Basic bayesian methods. Topics in Biostatistics, 2007: 319-338.

[10] Rusland N F, Wahid N, Kasim S, et al. Analysis of Naïve Bayes algorithm for email spam filtering across multiple datasets. conference series: materials science and engineering. IOP Publishing, 2017, 226(1): 012091.

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Published

18-02-2025

How to Cite

Zhou, Z. (2025). The Spam Email Filter Based on the Bayes Method. Highlights in Science, Engineering and Technology, 124, 229-232. https://doi.org/10.54097/03xmee88