  Streaming interactive proofs (SIPs) are a framework to reason about
outsourced computation, where a data owner (the verifier) outsources a
computation to the cloud (the prover), but wishes to verify the correctness of
the solution provided by the cloud service. In this paper we present streaming
interactive proofs for problems in data analysis. We present protocols for
clustering and shape fitting problems, as well as an improved protocol for
rectangular matrix multiplication. The latter can in turn be used to verify $k$
eigenvectors of a (streamed) $n \times n$ matrix. In general our solutions use
polylogarithmic rounds of communication and polylogarithmic total communication
and verifier space. For special cases (when optimality certificates can be
verified easily), we present constant round protocols with similar costs. For
rectangular matrix multiplication and eigenvector verification, our protocols
work in the more restricted annotated data streaming model, and use sublinear
(but not polylogarithmic) communication.
