Paper Info
Title
A Privacy-Preserving Outsourced Functional Computation Framework Across Large-Scale Multiple Encrypted Domains.
Abstract
In this paper, we propose a framework for privacy-preserving outsourced functional computation across large-scale multiple encrypted domains, which we refer to as POFD. With POFD, a user can obtain the output of a function computed over encrypted data from multiple domains while protecting the privacy of the function itself, its input and its output. Specifically, we introduce two notions of POFD, the basic POFD and its enhanced version, in order to tradeoff the levels of privacy protection and performance. We present three protocols, named Multi-domain Secure Multiplication protocol (MSM), Secure Exponent Calculation protocol with private Base (SECB), and Secure Exponent Calculation protocol ( SEC), as the core sub-protocols for POFD to securely compute the outsourced function. Detailed security analysis shows that the proposed POFD achieves the goal of calculating a user-defined function across different encrypted domains without privacy leakage to unauthorized parties. Our performance evaluations using simulations demonstrate the utility and the efficiency of POFD.
Year
DOI
Venue
2016
10.1109/TC.2016.2543220
IEEE Trans. Computers
Keywords
Field
DocType
Protocols,Privacy,Cloud computing,Data privacy,Public key cryptography,Encryption,Large-scale systems,Computational modeling,Outsourcing
Homomorphic encryption,Computer science,Computer security,Parallel computing,Theoretical computer science,Encryption,Multiplication,Security analysis,Information privacy,Public-key cryptography,Cloud computing,Computation
Journal
Volume
Issue
ISSN
65
12
0018-9340
Citations 
PageRank 
References 
4
0.41
29
Authors
5
Name
Order
Citations
PageRank
Ximeng Liu130452.09
Baodong Qin219019.40
R.H Deng34423362.82
Rongxing Lu45091301.87
Jianfeng Ma51336155.62