Publication Date
Spring 2017
Degree Type
Master's Project
Degree Name
Master of Science (MS)
Department
Computer Science
First Advisor
Mark Stamp
Second Advisor
Thomas Austin
Third Advisor
Aikaterini Potika
Keywords
image spam, machine learning
Abstract
Email is one of the most common forms of digital communication. Spam can be de ned as unsolicited bulk email, while image spam includes spam text embedded inside images. Image spam is used by spammers so as to evade text-based spam lters and hence it poses a threat to email based communication. In this research, we analyze image spam detection methods based on various combinations of image processing and machine learning techniques.
Recommended Citation
Chavda, Aneri, "Image Spam Detection" (2017). Master's Projects. 543.
DOI: https://doi.org/10.31979/etd.myqt-f92r
https://scholarworks.sjsu.edu/etd_projects/543
