Spherical classification for detecting malicious URL

For computer security it is useful to have some tools for detecting malicious URL. To this aim we introduce a binary classication method based on Spherical Separation, which handles information both on the URL syntax and its domain properties. In particular we adopt a simplied model which runs in O(t log t) time (t is the number of training samples) and thus it is suitable for large scale applications. We test our approach using dierent sets of features and report the results in terms of testing correctness according to the well-established ten-fold cross validation paradigm.