Bayesian Hill-Climbing Attack and Its Application to Signature Verification

A general hill-climbing attack algorithm based on Bayesian adaption is presented. The approach uses the scores provided by the matcher to adapt a global distribution computed from a development set of users, to the local specificities of the client being attacked. The proposed attack is evaluated on a competitive feature-based signature verification system over the 330 users of the MCYT database. The results show a very high-efficiency of the hill-climbing algorithm, which successfully bypassed the system for over 95% of the attacks.