University of Oulu

Juha Partala, “Symmetric Blind Decryption with Perfect Secrecy,” Journal of Computer Networks and Communications, vol. 2017, Article ID 6575907, 15 pages, 2017. doi:10.1155/2017/6575907

Symmetric blind decryption with perfect secrecy

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Author: Partala, Juha1
Organizations: 1Physiological Signal Analysis Team, The Center for Machine Vision and Signal Analysis, University of Oulu
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.7 MB)
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Language: English
Published: Hindawi, 2017
Publish Date: 2017-10-11


A blind decryption scheme enables a user to query decryptions from a decryption server without revealing information about the plain-text message. Such schemes are useful, for example, for the implementation of privacy-preserving encrypted file storages and payment systems. In terms of functionality, blind decryption is close to oblivious transfer. For noiseless channels, information-theoretically secure oblivious transfer is impossible. However, in this paper, we show that this is not the case for blind decryption. We formulate a definition of perfect secrecy of symmetric blind decryption for the following setting: at most one of the scheme participants is a passive adversary (honest-but-curious). We also devise a symmetric blind decryption scheme based on modular arithmetic on a ring Z𝑝2, where is a prime, and show that it satisfies our notion of perfect secrecy.

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Series: Journal of computer networks and communications
ISSN: 2090-7141
ISSN-E: 2090-715X
ISSN-L: 2090-7141
Volume: 2017
Article number: 6575907
DOI: 10.1155/2017/6575907
Type of Publication: A1 Journal article – refereed
Field of Science: 113 Computer and information sciences
Funding: Financial support from Infotech Oulu Graduate School and the following foundations is gratefully acknowledged: Finnish Foundation for Technology Promotion, the Nokia Foundation, Tauno Tönning Foundation, Walter Ahsltröm Foundation, and the Finnish Foundation for Economic and Technology Sciences (KAUTE).
Copyright information: Copyright © 2017 Juha Partala. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.