URL ATTACKS: Classification of URLs via Analysis and Learning

Abstract

Social Networks such as Twitter, Facebook play a remarkable growth in recent years. The ratio of tweets or messages in the form of URLs increases day by day. As the number of URL increases, the probability of fabrication also gets increased using their HTML content as well as by the usage of tiny URLs. It is important to classify the URLs by means of some modern techniques. Conditional redirection method is used here by which the URLs get classified and also the target page that the user needs is achieved. Learning methods also introduced to differentiate the URLs and there by the fabrication is not possible. Also the classifiers will efficiently detect the suspicious URLs using link analysis algorithm.