Publication Type

Conference Proceeding Article

Publication Date

5-2016

Abstract

In data outsourcing, a client stores a large amount of data on an untrusted server; subsequently, the client can request the server to compute a function on any subset of the data. This setting naturally leads to two security requirements: confidentiality of input data, and authenticity of computations. Existing approaches that satisfy both requirements simultaneously are built on fully homomorphic encryption, which involves expensive computation on the server and client and hence is impractical. In this paper, we propose two verifiable homomorphic encryption schemes that do not rely on fully homomorphic encryption. The first is a simple and efficient scheme for linear functions. The second scheme supports the class of multivariate quadratic functions, by combining the Paillier cryptosystem with a new homomorphic message authentication code (MAC) scheme. Through formal security analysis, we show that the schemes are semantically secure and unforgeable.

Keywords

Data outsourcing, Homomorphic encryption, Homomorphic MAC, Verifiable computation

Discipline

Databases and Information Systems | Information Security

Research Areas

Data Management and Analytics; Cybersecurity

Publication

Asia CCS '16: Proceedings of the 11th ACM Asia Conference on Computer and Communications Security, Xi'an, China, May 30 - June 3

First Page

605

Last Page

616

ISBN

9781450342339

Identifier

10.1145/2897845.2897892

Publisher

ACM

City or Country

New York

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

https://doi.org/10.1145/2897845.2897892

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