Chapter 5 Fake Email and Spam Detection: User Feedback with Naives Bayesian Approach Ayushi Gupta, Sushila Palwe and Devyani Keskar 1 Introduction In neoteric times, amongst the quickest and majorly reasonable methods of intercom- munication in the society for interaction and conversing with parents and friends and for exchanging files, data, etc., emails are being used. They are segregated into dis- tinct categories like ham (solicited) or spam (unsolicited). The classification which deals with legal, authorized and verified emails falls under ham mails, whereas on the other hand, the category which accounts to fake, unwanted, useless and pointless mails comes under spam mails. Thus, these unwanted are causing major problems and dire consequences. Amidst these, the rooted spam emails are crucial as they embezzle storage space, generate time wastage, induce harmful malware and cru- cially affect phishing. Issues like resource consumption, transmission bandwidth costs, user’s time wastage, etc., cost billions of dollars. Segregation of spam mails at real time is deployed and performed by Naive Bayes method. The major work carried out by a classifier is to recognize the unwanted, fake or harmful mails which are sent to the user and characterize it as unsolicited (spam) mail. A. Gupta (B ) · D. Keskar Department of Computer Engineering, MITCOE, Pune, India e-mail: ayushimg9@gmail.com D. Keskar e-mail: devyani.keskar@gmail.com S. Palwe School of CET, MITWPU, Pune, India e-mail: sushila.palwe@mitwpu.edu.in © Springer Nature Singapore Pte Ltd. 2020 S. Bhalla et al. (eds.), Proceeding of International Conference on Computational Science and Applications, Algorithms for Intelligent Systems, https://doi.org/10.1007/978-981-15-0790-8_5 41