Master of Science (MS)
Fabio Di Troia
Spam can be defined as unsolicited bulk email. In an effort to evade text-based spam filters, spammers can embed their spam text in an image, which is referred to as image spam. In this research, we consider the problem of image spam detection, based on image analysis. We apply various machine learning and deep learning techniques to real-world image spam datasets, and to a challenge image spam-like dataset. We obtain results comparable to previous work for the real-world datasets, while our deep learning approach yields the best results to date for the challenge dataset.
Sharmin, Tazmina, "Deep Learning for Image Spam Detection" (2019). Master's Projects. 702.
Available for download on Wednesday, May 20, 2020