On rough sets and inference analysis

Abstract

In this paper, we give an overview of a promising approach to inference detection and analysis in relational databases, first introduced in [25]. The approach employs techniques from rough sets theory and is able to take into account of all certain and possible material implications in the data, including functional dependencies. It can also be used to address inference threats posed by rule-induction techniques from data mining. A major advantage of this approach is that the quantitative measure IRI is computed directly from data without knowledge input from System Security Officer. By comparing with other techniques, we attempt to convey the merits of rough sets based approach.