Belief Reasoning in MLS Deductive Databases

摘要

It is envisaged that the application of the multilevel security (MLS) scheme will enhance flexibility and effectiveness of authorization policies in shared enterprise databases and will replace cumbersome authorization enforcement practices through complicated view definitions on a per user basis. However, as advances in this area are being made and ideas crystallized, the concomitant weaknesses of the MLS databases are also surfacing. We insist that the critical problem with the current model is that 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 different 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 way. To this end, we develop a function to compute belief in multiple modes which can be used to reason about the beliefs of other users. We strive to develop a poised and practical logical characterization of MLS databases for the first time based on the inherently difficult 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.