Abdul Kareem, Razia Sulthana ORCID: 0000-0001-5331-1310, Verma, Avani and Abdul Kareem, Jaithunbi (2022) A detailed analysis on spam emails and detection using Machine Learning algorithms. In: Conference Proceedings Inventive Systems and Control. Springer. (In Press)

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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:	Conference Proceedings Inventive Systems and Control
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)
Related URLs:	Publisher Publisher
Last Modified:	19 May 2023 15:10
URI:	http://gala.gre.ac.uk/id/eprint/41815

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