Person:

Chong, Stephen

We explore the inference of expressive human-readable declassification policies as a step towards providing practical tools and techniques for strong language-based information security. Security-type systems can enforce expressive information-security policies, but can require enormous programmer effort before any security benefit is realized. To reduce the burden on the programmer, we focus on inference of expressive yet intuitive information-security policies from programs with few programmer annotations. We define a novel security policy language that can express what information a program may release, under what conditions (or, when) such release may occur, and which procedures are involved with the release (or, where in the code the release occur). We describe a dataflow analysis for precisely inferring these policies, and build a tool that instantiates this analysis for the Java programming language. We validate the policies, analysis, and our implementation by applying the tool to a collection of simple Java programs.