When handling large quantities of data, it is desirable to outsource the computational effort to a third party: this captures current efforts in cloud computing, but also scenarios within trusted computing systems and inter-organizational data sharing. When the third party is not fully trusted, it is desirable to give assurance that the computation has been perfomed correctly. This talk presents some recent results in designing new protocols for verifying computations which are streaming in nature: the verifier (data owner) needs only a single pass over the input, storing a sublinear amount of information, and follows a simple protocol with a prover (serice provider) that takes a small number of rounds. A dishonest prover fools the verifier with only polynomially small probabiliy, while an honest prover's answer is always accepted. Within this model, we show protocols for a variety of problems that select items from the input (e.g. median, heavy hitters), or compute certain aggregates or structures (e.g. frequency moments, number of triangles in a graph). These problems require linear space to compute (exactly) in the traditional streaming model, showing that outsourcing can exponentially reduce the effort needed by the verifier to obtain correct answers.
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