1,249 research outputs found
Cloud Data Auditing Using Proofs of Retrievability
Cloud servers offer data outsourcing facility to their clients. A client
outsources her data without having any copy at her end. Therefore, she needs a
guarantee that her data are not modified by the server which may be malicious.
Data auditing is performed on the outsourced data to resolve this issue.
Moreover, the client may want all her data to be stored untampered. In this
chapter, we describe proofs of retrievability (POR) that convince the client
about the integrity of all her data.Comment: A version has been published as a book chapter in Guide to Security
Assurance for Cloud Computing (Springer International Publishing Switzerland
2015
Private Outsourcing of Polynomial Evaluation and Matrix Multiplication using Multilinear Maps
{\em Verifiable computation} (VC) allows a computationally weak client to
outsource the evaluation of a function on many inputs to a powerful but
untrusted server. The client invests a large amount of off-line computation and
gives an encoding of its function to the server. The server returns both an
evaluation of the function on the client's input and a proof such that the
client can verify the evaluation using substantially less effort than doing the
evaluation on its own. We consider how to privately outsource computations
using {\em privacy preserving} VC schemes whose executions reveal no
information on the client's input or function to the server. We construct VC
schemes with {\em input privacy} for univariate polynomial evaluation and
matrix multiplication and then extend them such that the {\em function privacy}
is also achieved. Our tool is the recently developed {mutilinear maps}. The
proposed VC schemes can be used in outsourcing {private information retrieval
(PIR)}.Comment: 23 pages, A preliminary version appears in the 12th International
Conference on Cryptology and Network Security (CANS 2013
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