Belief reasoning in MLS deductive databases
It is envisaged that the application of the multilevel security (MLS) scheme will enhance exibility and e ectiveness of authorization policies in shared enterprise databases and will replace cumbersome authorization enforcement practices through complicated view de nitions on a per user basis. However, as advances in this area are being made and ideas crystallized, the concomitant w eaknesses of the MLS databases are also surfacing. We insist that the critical problem with the current model is
... hat the belief at a higher security level is cluttered with irrelevant or inconsistent data as no mechanism for attenuation is supported. Critics also argue that it is imperative for MLS database users to theorize about the belief of others, perhaps at di erent security levels, an apparatus that is currently missing and the absence of which is seriously felt. The impetus for our current research is this need to provide an adequate framework for belief reasoning in MLS databases. We demonstrate that a prudent application of the concept of inheritance in a deductive database setting will help capture the notion of declarative belief and belief reasoning in MLS databases in an elegant w ay. T o this end, we d e v elop a function to compute belief in multiple modes which can be used to reason about the beliefs of other users. We strive t o d e v elop a poised and practical logical characterization of MLS databases for the rst time based on the inherently di cult concept of non-monotonic inheritance. We present an extension of the acclaimed Datalog language, called the MultiLog, and show that Datalog is a special case of our language. We also suggest an implementation scheme for MultiLog as a front-end for CORAL.