Intelligent Assistant for Context-Aware Policies

Abstract

Recent advancements in document handling tools have greatly simplified the tasks of reusing content and copying between secure and unsecure locations. As a result, intentional and unintentional data leaks are occurring more often and so posing a serious risk. To address this issue, context-aware policies have been introduced so that the policies pertain to the patterns of text contained in actual run-time content - as well as static document-level metadata with the aim of distinguishing different types of sensitive documents. Unlike traditional metadata based policies, context-aware policies do not need to have any overlap in their conditions for contradictions to occur, which makes it harder to create and manage coherent, ambiguity free sets of policies. We provide a novel Intelligent Modeling Assistant (IMA) that automatically deals with resolvable complications in modelling, while breaking tasks requiring manual intervention into a set of simple decisions. The IMA also helps the administrator to understand possible consequences of policies through sets of examples. Our implementation using constraint satisfaction technology is described.