A Survey on Detecting Suspicious and Malicious URLs in E-mail and Social Networks - Dhanashri, Vispute; Bhagyashri, Vispute; Monika, Sonawane; Seema, Nikam (International Journal of Computer Sciences and Engineering, 2025)
These days, Email is also one of the advertising medium. Though it is a healthy medium for advertising, this is getting misused also. It gets really inconvenient to attend all those unnecessary emails. It is also very distracting. Here we are proposing a solution as email classifier. It will classify the inbox emails into various categories. A selected category of emails can be blocked considering it spam. In this study, the features of traditional heuristics and social networking are presented by combining them in feature set. This is done with Bayesian algorithm, know very helpful in such text classification tasks. The experimental result shows that the high detection rate is achieved by proposed approach. In this by using reduced feature set method we identify malicious URLs in email.