Sulthana, Razia ORCID: 0000-0001-5331-1310, Verma, Avani and Jaithunbi, A. K. (2023) A detailed analysis on spam emails and detection using machine learning algorithms. In: Inventive Systems and Control Proceedings of ICISC 2023. Lecture Notes in Networks and Systems, 672 . Springer, pp. 65-76. ISBN 9789819916238 ISSN 2367-3370 (Print), 2367-3389 (Online) (doi:https://doi.org/10.1007/978-981-99-1624-5_5)

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Abstract

Spam email is the unwanted junk and solicited email sent in
bulk to the receivers, using botnets, spambots, or a network of infected computers. These spam emails can be phishing emails that trick users to get their sensitive information, download malware into the user devices or scam the users stealing confidential data. This paper shows a systematic analysis of spam and its types. It also details the procedure
of how the spammers get the email addresses of the receivers. It analyses the problems with spamming. A detailed state of the art on spam filters and the factors that put an email into the spam or ham category is also explained. The paper also discusses spam filtering methods of Gmail, Yahoo, and Outlook. Finally, it brings out several solutions to detect spam
using principles of Machine Learning and Data Mining

Item Type:	Conference Proceedings
Title of Proceedings:	Inventive Systems and Control Proceedings of ICISC 2023
Uncontrolled Keywords:	security breach, Naive bayes, logistic regression, machine learning
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Last Modified:	27 Jun 2023 09:52
URI:	http://gala.gre.ac.uk/id/eprint/41815

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