Abstract: If there are pros, corns are always there. As email becomes a part of individual’s need in our busy life with its benefits, it has negative aspect too by means of email spamming. Nowadays images with embedded text called image spamming have been used by the spammers as effective text spam filtering methods already been introduced. Tracking and stopping spam become challenge in the internet world because of versatility in the spam images. In this paper a novel model AFSIF (Autonomous Fuzzy Spam Image Filter) has been introduced. The basic idea behind AFSIF is, an spam image can combine several basic features of different spam images, so feature fusion weight of the image has been generated, which keeps combined feature of spam images and user preference as well. Here user preference has not been applied separately; it is used to calculate the fusion weight in terms of predefined topics (rule table).

Master Prince, “Clustering-based Spam Image Filtering Considering Fuzziness of the Spam Image” International Journal of Advanced Computer Science and Applications(IJACSA), 7(12), 2016. http://dx.doi.org/10.14569/IJACSA.2016.071234

@article{Prince2016,
title = {Clustering-based Spam Image Filtering Considering Fuzziness of the Spam Image},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.071234},
url = {http://dx.doi.org/10.14569/IJACSA.2016.071234},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {12},
author = {Master Prince}
}