A Bayesian network approach to detecting privacy intrusion

Personal information privacy could be compromised during information collection, transmission, and handling. In information handling, privacy could be violated by both the inside and the outside intruders. Though, within an organization, private data are generally protected by the organization's privacy policies and the corresponding platforms for privacy practices, private data could still be misused intentionally or unintentionally by individuals who have legitimate access to them in the organization. In this paper we propose a Bayesian network-based method for insider privacy intrusion detection in database systems.