As huge amount of personal data collected into databases of service providers increase, so does the risk of private information disclosure. Recently, a number of privacy-preserving techniques have been proposed, however, they are either pre-controls or post-controls and limited in protection of privacy without information loss or distortion, quite a few techniques can be seen among literatures for detecting information disclosure in the process of data transmission. In this paper, we focus on disclosure detection related to database publishing, and present a novel approach of detecting privacy leakages over data streams on querying databases by using dynamic pattern matching and data stream processing techniques. Experimental results via Cayuga system verified the feasibility of our proposal.