Culminating Project Title
Date of Award
Culminating Project Type
Information Assurance: M.S.
Information Assurance and Information Systems
Herberger School of Business
Prof. Abdullah Abu Hussein
Dr. Lynn Collen
Prof. Sneh Kalia
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Keywords and Subject Headings
Junk, Unsolicited, Ham, Detection, Evaluating, Spam, Accuracy
Email has become a vital form of communication among individuals and organizations in today’s world. However, simultaneously it became a threat to many users in the form of spam emails which are also referred as junk/unsolicited emails. Most of the spam emails received by the users are in the form of commercial advertising, which usually carry computer viruses without any notifications. Today, 95% of the email messages across the world are believed to be spam, therefore it is essential to develop spam detection techniques. There are different techniques to detect and filter the spam emails, but off recently all the developed techniques are being implemented successfully to minimize the threats. This paper describes how the current spam email detection approaches are determining and evaluating the problems. There are different types of techniques developed based on Reputation, Origin, Words, Multimedia, Textual, Community, Rules, Hybrid, Machine learning, Fingerprint, Social networks, Protocols, Traffic analysis, OCR techniques, Low-level features, and many other techniques. All these filtering techniques are developed to detect and evaluate spam emails. Along with classification of the email messages into spam or ham, this paper also demonstrates the effectiveness and accuracy of the spam detection techniques.
Guda, Seshi Reddy, "Evaluation of Email Spam Detection Techniques" (2022). Culminating Projects in Information Assurance. 125.