Document Type
Dissertation
Major/Program
Computer Science
First Advisor's Name
Geoffrey Smith
First Advisor's Committee Title
Committee Chair
Second Advisor's Name
Jinpeng Wei
Third Advisor's Name
Peter Clarke
Fourth Advisor's Name
Dev Roy
Date of Defense
2-28-2011
Abstract
Type systems for secure information flow aim to prevent a program from leaking information from H (high) to L (low) variables. Traditionally, bisimulation has been the prevalent technique for proving the soundness of such systems. This work intro- duces a new proof technique based on stripping and fast simulation, and shows that it can be applied in a number of cases where bisimulation fails. We present a progressive development of this technique over a representative sample of languages includ- ing a simple imperative language (core theory), a multiprocessing nondeterministic language, a probabilistic language, and a language with cryptographic primitives.
In the core theory we illustrate the key concepts of this technique in a basic setting. A fast low simulation in the context of transition systems is a binary relation where simulating states can match the moves of simulated states while maintaining the equivalence of low variables; stripping is a function that removes high commands from programs. We show that we can prove secure information flow by arguing that the stripping relation is a fast low simulation.
We then extend the core theory to an abstract distributed language under a nondeterministic scheduler. Next, we extend to a probabilistic language with a random assignment command; we generalize fast simulation to the setting of discrete time Markov Chains, and prove approximate probabilistic noninterference. Finally, we introduce cryptographic primitives into the probabilistic language and prove computational noninterference, provided that the underling encryption scheme is secure.
Identifier
FI11042705
Recommended Citation
Alpizar, Rafael H., "Secure Information Flow via Stripping and Fast Simulation" (2011). FIU Electronic Theses and Dissertations. 366.
https://digitalcommons.fiu.edu/etd/366
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