Authenticable data analytics over encrypted data in the cloud

Publication Type

Journal Article

Publication Date

1-2023

Abstract

Statistical analytics on encrypted data requires a fully-homomorphic encryption (FHE) scheme. However, heavy computation overheads make FHE impractical. In this paper we propose a novel approach to achieve privacy-preserving statistical analysis on an encrypted database. The main idea of this work is to construct a privacy-preserving calculator to calculate attributes’ count values for later statistical analysis. To authenticate these encrypted count values, we adopt an authenticable additive homomorphic encryption scheme to construct the calculator. We formalize the notion of an authenticable privacy-preserving calculator that has properties of broadcasting and additive homomorphism. Further, we propose a cryptosystem based on binary vectors to achieve complex logic expressions for statistical analysis on encrypted data. With the aid of the proposed cryptographic calculator, we design several protocols for statistical analysis including conjunctive, disjunctive and complex logic expressions to achieve more complicated statistical functionalities. Experimental results show that the proposed scheme is feasible and practical.

Keywords

Encrypted data, authenticable encryption, data privacy, homomorphic encryption

Discipline

Information Security | Numerical Analysis and Scientific Computing

Research Areas

Cybersecurity

Publication

IEEE Transactions on Information Forensics and Security

ISSN

1556-6013

Identifier

10.1109/TIFS.2023.3256132

Publisher

Institute of Electrical and Electronics Engineers

Additional URL

https://doi.org/10.1109/TIFS.2023.3256132

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