Contact Project Developer Ashish D. Tiwari [astiwz@gmail.com]
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Publicly Verifiable Inner Product Evaluation over Outsourced Data Streams under Multiple Keys

Publicly Verifiable Inner Product Evaluation over Outsourced Data Streams under Multiple Keys
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Publicly Verifiable Inner Product Evaluation over Outsourced Data Streams under Multiple Keys


Abstract Uploading data streams to a resource-rich cloud server for inner product evaluation, an essential building block in many popular stream applications (e.g., statistical monitoring), is appealing to many companies and individuals. On the other hand, verifying the result of the remote computation plays a crucial role in addressing the issue of trust. Since the outsourced data collection likely comes from multiple data sources, it is desired for the system to be able to pinpoint the originator of errors by allotting each data source a unique secret key, which requires the inner product verification to be performed under any two parties’ different keys. However, the present solutions either depend on a single key assumption or powerful yet practically inefficient fully homomorphic cryptosystems. In this paper, we focus on the more challenging multi-key scenario where data streams are uploaded by multiple data sources with distinct keys. We first present a novel homomorphic verifiable tag technique to publicly verify the outsourced inner product computation on the dynamic data streams, and then extend it to support the verification of matrix product computation. We prove the security of our scheme in the random oracle model. Moreover, the experimental result also shows the practicability of our design.

Architecture:


PROPOSED SYSTEM:

Proposed a realization of homomorphic signatures for bounded constant degree polynomials based on hard problems on ideal lattices. Although not all the above schemes are explicitly presented in the context of streaming data, they can be applied there under a single-key setting. In this scenario, the data source continually generates and outsources authenticated data values to a third-party server.

           However, the outsourced data to be a priori fixed. Another interesting line of works considered a different setting for verifiable computation. Clients are only allowed to query the server for the summation of a grouped data specified by the data source. A scheme of outsourced computations including groupby sum, inner product, and matrix product with private verifiability was considered.


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