Identity-based remote data integrity checking with perfect data privacy preserving for cloud storage
Yu, Y; Au, MH; Ateniese, G; et al.Huang, X; Susilo, W; Dai, Y; Min, G
Date: 1 April 2017
Journal
IEEE Transactions on Information Forensics and Security
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Publisher DOI
Abstract
Remote data integrity checking (RDIC) enables a
data storage server, such as a cloud server, to prove to a
verifier that it is actually storing a data owner’s data honestly.
To date, a number of RDIC protocols have been proposed in
the literature, but almost all the constructions suffer from the
issue of a complex key management, ...
Remote data integrity checking (RDIC) enables a
data storage server, such as a cloud server, to prove to a
verifier that it is actually storing a data owner’s data honestly.
To date, a number of RDIC protocols have been proposed in
the literature, but almost all the constructions suffer from the
issue of a complex key management, that is, they rely on the
expensive public key infrastructure (PKI), which might hinder
the deployment of RDIC in practice. In this paper, we propose
a new construction of identity-based (ID-based) RDIC protocol
by making use of key-homomorphic cryptographic primitive
to reduce the system complexity and the cost for establishing
and managing the public key authentication framework in PKI
based RDIC schemes. We formalize ID-based RDIC and its
security model including security against a malicious cloud server
and zero knowledge privacy against a third party verifier. We
then provide a concrete construction of ID-based RDIC scheme
which leaks no information of the stored files to the verifier
during the RDIC process. The new construction is proven secure
against the malicious server in the generic group model and
achieves zero knowledge privacy against a verifier. Extensive
security analysis and implementation results demonstrate that
the proposed new protocol is provably secure and practical in
the real-world applications.
Computer Science
Faculty of Environment, Science and Economy
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