Abstract
We present an inclusive review of recent and successful content-based e-mail spam filtering techniques. Our focus is mainly on machine learning-based spam filters and variants inspired from them. We report on relevant ideas, techniques, taxonomy, major efforts, and the state-of-the-art in the field. The initial interpretation of the prior work examines the basics of e-mail spam filtering and feature engineering. We conclude by studying techniques, evaluation benchmarks, and explore the promising offshoots of latest developments and suggest lines of future investigations.
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Bhowmick, A., Hazarika, S.M. (2018). E-Mail Spam Filtering: A Review of Techniques and Trends. In: Kalam, A., Das, S., Sharma, K. (eds) Advances in Electronics, Communication and Computing. Lecture Notes in Electrical Engineering, vol 443. Springer, Singapore. https://doi.org/10.1007/978-981-10-4765-7_61
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DOI: https://doi.org/10.1007/978-981-10-4765-7_61
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