The Repository @ St. Cloud State

Open Access Knowledge and Scholarship

Date of Award


Culminating Project Type

Starred Paper



Degree Name

Information Assurance: M.S.


Information Assurance and Information Systems


Herberger School of Business

First Advisor

Prof. Abdullah Abu Hussein

Second Advisor

Dr. Lynn Collen

Third Advisor

Prof. Sneh Kalia

Creative Commons License

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.


I am thankful and would like to convey my gratitude to every individual who has helped me with their inputs in the accomplishment of my Starred Paper. Primarily, I am thankful to Professor Abdullah Abu Hussein, who is the chairperson and advisor of my Starred Paper Committee. He provided valuable guidance wherever required and assisted me throughout the completion of my study. I am also thankful to Dr. Sneh Kalia and Dr. Lynn Collen for their support and guidance in my research study, who are also the members of my Starred Paper Committee. I am grateful to Professor Abdullah Abu Hussein, who assisted me with his insightful suggestions and comments throughout my study.

Lastly, I am grateful to the library staff of St. Cloud State University for providing their resources which helped me during my study.