Image Spam Detection through Pattern Recognition with IP Tracing Technique

Image spam is a kind of E-mail spam where the message text of the spam is presented as a picture in an image file. The basic rationale behind image spam is difficult to detect using text spam filtering methods which is designed to detect patterns in text in the plain-text E-mail body or attachments. A new trend in email spam is the emergence of image spam. The most previous works of image spam detection focused on filtering the image spam on the client side. This proposed system considered more desirable comprehensive solution which embraces the both server side filtering and client side detection methods. The spectral clustering algorithm is introduced to similarity measure for cluster analysis of spam images to filter the attack activities of spammers and fast trace back the spam sources. The active learning algorithm is limited where the learner guides the users to label as few images as possible while maximizing the classification accuracy.