Image Spam Filtering Method Based on Base64 Encoding
Congfu Xu · Jisuanji gongcheng · 2011
Extracting embedded text from images to filter image spam is usually time-consuming and can not reach high classification accuracy.On the other hand,filtering image spam using image properties features has low recall rates problem.This paper proposes a simple but effective method to detect image spam.By tokenizing Base64-encoded image text into a series of 4-gram features and representing them as a binary vector,a trained Support Vector Machine(SVM) can distinguish spam images from legitimate ones very well.Experimental results show that the method achieves satisfactory performance in filtering image spam with different formats,with the precision,recall and F1 of 99.85%,99.49% and 99.67% respectively.