Indistinguishability Obfuscation for Turing Machines with Unbounded Memory
- Brent Waters | University of Texas at Austin
We show how to build indistinguishability obfuscation (iO) for Turing Machines where the overhead is polynomial in the security parameter lambda, machine description |M| and input size |x| (with only a negligible correctness error). In particular, we avoid growing polynomially with the maximum space of a computation. Our construction is based on iO for circuits, one way functions and injective pseudo random generators. Our results are based on new ”selective enforcement” techniques. Here we first create a primitive called positional accumulators that allows for a small commitment to a much larger storage. The commitment is unconditionally sound for a select piece of the storage. This primitive serves as an ”iO-friendly” tool that allows us to make two different programs equivalent at different stages of a proof. The pieces of storage that are selected depend on what hybrid stage we are at in a proof. We first build up our enforcement ideas in a simpler context of ”message hiding encodings” and work our way up to indistinguishability obfuscation. Joint work with Allison Bishop Lewko and Venkata Koppula.
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Melissa Chase
Principal Researcher
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