A Review Article On Enhancing Email Spam Filter’s Accuracy Using Machine Learning

Livingston Jeeva, Ijtaba Saleem Khan

doi:10.55524/ijircst.2023.11.4.2

Abstract

In today’s era, almost everyone is using emails on their daily basis. In our proposed research, we suggest a machine learning-based strategy for enhancing email spam filters' accuracy. Traditional rule-based filters have grown less effective as spam emails have multiplied exponentially. Models can be trained to identify emails as spam or not using machine learning algorithms, particularly supervised learning. We need to create a simple and straightforward machine learning model in order to reach more accurate results while categorizing email spam. We picked the Naive Bayes technique for our model since it is quicker and more accurate than other algorithms. The suggested method can have incorporated into current email systems to enhance spam filtering functionality. This review paper provides an overview of the machine learning model we have suggested.

Keywords

Naïve Bayes, Email Spam, Filter, Accuracy, Classification, Machine Learning

References

[1] Ahmed, N., Hussain, M., Saleem, K., & Shah, S. A. (2022). Evaluation and Research Challenges for Spam Detection Using Machine Learning Techniques in IoT and Email Platforms. IEEE Internet of Things Journal, 9(4), 2868-2879.

[2] Raza, M., Shahid, M., & Raza, A. (2021). A Complete Review on Classifying Email Spam Using Machine Learning Models. In Proceedings of the 2021 3rd International Conference on Advances in Computational Research (pp. 1-6).

[3] Bhuiyan, H., Ahmed, K., & Shahrear, P. (2018). A Review of Current Email Spam Filtering Methods Taking Machine Learning Techniques into Consideration. Journal of Computer Science and Technology, 18(1), 1-13.

[4] Dada, E. G., Omidiora, E. O., Olawumi, T. O., & Misra, S. (2019). Review, methods, and unsolved issues in the use of machine learning for email spam filtration. Journal of Ambient Intelligence and Humanized Computing, 10(3), 1093-1115.

[5] Huang, L., Li, Y., & Li, W. (2018). Intelligent Text Mutation Detection to Improve the Naive Bayes email Filter. IEEE Access, 6, 50128-50139.

[6] Mathur, A., Singh, P., & Choudhary, S. (2015). Spam Detection Techniques: Issues and Challenges. International Journal of Computer Applications, 113(4), 36-39.

[7] Agarwal, K., Rastogi, M., & Bisht, N. (2018). Using a combined method of Naive Bayes and Particle Swarm Optimization, email spam detection. Journal of Computer Science and Applications, 6(2), 50-55.

[8] Nandhini, S., Padma, P., & Vaithiyanathan, V. (2020). Performance Assessment of Machine Learning Approaches for Detecting Email Spam. In Advances in Intelligent Systems and Computing (Vol. 1153, pp. 45-52). Springer.

[9] Kumar, N., Singh, P., & Singh, A. K. (2020). Email Spam Detection Using Machine Learning Algorithms. In Proceedings of the 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT) (pp. 1-5).

[10] Samira, S., Ghazi, S., & Berrouk, A. S. (2020). Hybrid Artificial Intelligence Model for Email Spam Detection. In 2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI) (pp. 1-6).

[11] Email Spam Detection Techniques: A Comprehensive Review. Journal of Computer Science and Technology, 19(1), 1-16.

[12] A Survey on Machine Learning Techniques for Email Spam Filtering. International Journal of Advanced Research in Computer Science, 10(5), 94-98.

[13] A Novel Hybrid Method for Email Spam Detection Based on Machine Learning and Rule-Based Approaches. Journal of Information Processing Systems, 16(2), 372-385.

[14] A Model Pairing Machine Learning and Deep Learning for Email Spam Detection. In events of the 2020 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA) (pp. 598-604).

[15] An Efficient Email Spam Detection System Using Machine Learning and Natural Language Processing. International Journal of Advanced Computer Science and Applications, 11(1), 6-11.

[16] Email Spam Detection Using Machine Learning: A Comparative Study. International Journal of Computer Applications, 180(38), 9-16.

[17] A Review of Email Spam Detection Techniques Based on Machine Learning and Deep Learning. In Advances in Computational Intelligence (pp. 39-49). Springer, Singapore.

[18] A Hybrid Model for Email Spam Detection Using Machine Learning and Graph Mining Techniques. Journal of Ambient Intelligence and Humanized Computing, 12(7), 6035-6046.

[19] Email Spam Detection Using Machine Learning Techniques: A Comparative Study. In Proceedings of the 2022 International Conference on Advanced Computing and Intelligent Engineering (ICACIE) (pp. 495-500).

[20] Email Spam Detection Using Ensemble Machine Learning Algorithms. Journal of King Saud University-Computer and Information Sciences, 34(5), 634-642.

[21] Gopalakrishnan, N., & Ramanathan, R. (2019). Comparative study of different machine learning algorithms for email spam detection. International Journal of Engineering and Advanced Technology, 8(3), 988-991.

[22] Priyanka, M., & Hemalatha, K. (2019). Survey of email spam detection techniques using machine learning. International Journal of Computer Science and Information Technology Research, 7(3), 57-64.

[23] Haleem, M. S., & Farooq, U. (2019). Empirical study of email spam detection using machine learning and deep learning techniques. International Journal of Scientific and Research Publications, 9(6), 33-37.

[24] Sharma, N., & Chauhan, S. S. (2020). Improved email spam detection system using machine learning and deep learning. International Journal of Computer Applications, 174(13), 1-7.

[25] Gideon, G. O., & Adeloye, A. A. (2020). Deep learning approach for email spam detection. Journal of Computer Science and Information Technology, 8(1), 1-9.

[26] Ali, M., Ali, I., & Ahmad, T. (2020). Hybrid model for email spam detection using machine learning and natural language processing techniques. International Journal of Scientific Research in Computer Science and Engineering, 8(1), 19-25.

[27] Gupta, P. K., & Rao, K. S. (2020). Email spam detection using machine learning and feature selection techniques. International Journal of Advanced Computer Science and Applications, 11(2), 72-77.

[28] Sudha, S., & Hemalatha, K. (2021). Review of email spam detection using machine learning techniques. International Journal of Innovative Technology and Exploring Engineering, 10(7S), 124-128.

[29] Divya, A., Sindhuja, B., & Thangavelu, K. (2021). Comparative study of machine learning and text mining techniques for email spam detection. International Journal of Advanced Science and Technology, 30(2), 4705-4714.

[30] Yan, R., Cai, Z., & Zhang, X. (2021). Novel email spam detection model based on ensemble learning and natural language processing. International Journal of Advanced Trends in Computer Science and Engineering, 10(5), 1-8.

[31] Haraty, R. A., & Saeed, K. (2021). Comprehensive review of machine learning and deep learning techniques for email spam detection. International Journal of Computer Science and Mobile Computing, 10(6), 107-113.

[32] Dwivedi, A., & Kumar, R. (2022). Comparative study of machine learning techniques for email spam detection. International Journal of Information and Computing Science, 2(1), 14-20.

[33] Al-Sewari, M. H. N., & Zummo, S. A. (2022). Systematic literature review of email spam detection using machine learning and deep learning techniques. International Journal of Artificial Intelligence and Data Mining, 2(1), 38-56.

[34] Islam, M. R., & Kabir, M. H. (2022). Novel approach for email spam detection using deep learning techniques and feature engineering. International Journal of Advanced Computer Science and Applications, 13(1), 295-301.

[35] Pooja, M. M., & Swathi, P. S. (2023). Comparative study of machine learning and natural language processing techniques for email spam detection. International Journal of Computer Science and Mobile Computing, 12(2), 58-65

Cites this article as

[Livingston Jeeva, Ijtaba Saleem Khan (2023), A Review Article On Enhancing Email Spam Filter’s Accuracy Using Machine Learning, International Journal of Innovative Research in Computer Science and Technology (IJIRCST), Vol-11, Issue-4, Page No-5-11], (ISSN 2347 - 5552). www.ijircst.org

Corresponding Author

Livingston Jeeva

M.Tech. Scholar, Department of Computer Science and Engineering, Integral University, Lucknow, India

Download Full Paper

Download PDF

No. of Downloads: 34 | No. of Views: 2492

An Identified Kidney Cancer Using Decision Tree and Naïve Bayes Algorithm in Data Mining

Shrikrishna S Balwante, Dr Mona Dwivedi.

September 2023 - Vol 11, Issue 5
Systematic Review of the Association between Cancer-Related Dementia and Mality: Systematic Review and Meta-Analysis

Chirag Varshney, Priyal Mittal, Mayank Bishra, Dr Yojna Arora.

July 2023 - Vol 11, Issue 4
Fire Alarm System Through Smoke Detection

Manya Sinha, Shivank Solanki, Sudeep Batra, Dr. Yojna Arora, Abhishek Tewatia.

July 2023 - Vol 11, Issue 4

IJIRCST

A Review Article On Enhancing Email Spam Filter’s Accuracy Using Machine Learning

Citations

Download Full Paper PDF

Total View 2492

Total Download 34