Security of random data perturbation methods

Statistical databases often use random data perturbation (RDP) methods to p rotect against disclosure of confidential numerical attributes. One of the key requirements of RDP methods is that they provide the appropriate level of security against snoopers who attempt to obtain information on confident ial attributes through statistical inference. In this study, we evaluate th e security provided by three methods of perturbation. The results of this s tudy allow the database administrator to select the most effective RDP meth od that assures adequate protection against disclosure of confidential info rmation.