Data Level Inference Detection in Database Systems

Existing work on inference detection for database systems mainly employ functional dependencies in the database schema to detect inferences. It has been noticed that analyzing the data stored in the database may help to detect more inferences. In this paper, we describe our e ort in developing a data level inference detection system. We have identi ed ve inference rules that a user can use to perform inferences. They are `subsume', `unique characteristic', `overlapping', `complementary', and `functional dependency' inference rules. The existence of these inference rules con rms the inadequacy of detecting inferences using just functional dependencies. The rules can be applied any number of times and in any order. These inference rules are sound. They are not necessarily complete, although we have no example that demonstrates incompleteness. We employ a rule based approach so that future inference rules can be incorporated into the detection system. We have dev...

• Type: Conference
• Year: 1998
• Where: CSFW
• Authors: Raymond W. Yip, Karl N. Levitt
• Keywords: CSFW 1998, Inference, Inference Detection, Inference Rules, Security Privacy