UBSF: A novel online URL-Based Spam Filter

Spam fighting is a classic puzzle in network security. In the past decades, many filtering spam solutions have been proposed. However, currently the conventional techniques still suffer from high false positives and false negatives, especially the former which usually cannot be accepted by the end users. This paper proposes a novel online URL-based spam filter (UBSF) on the basis of analyses over the conventional especially the URL-based anti-spam techniques. UBSF identifies spam by comparing the similarity of the extracted URLs (universal resource locator) from them with the URLs from our user-oriented standard URL Library (SUL). Experimental evaluations both from the contrast experiment and the prototype based on UBSF demonstrate it can significantly raise the filtering accuracy, effectively reduce false positives and can be applied to online process and heavy traffic environment by reducing the computational cost than the state-of-the-art techniques.