Paper Info
Title
Distributed compressed sensing for multi-sourced fusion and secure signal processing in private cloud
Abstract
Abstract In this paper, a novel scheme is proposed for multi-sourced signal fusion and secure processing. Within a distributed compressed sensing (DCS) framework, traditional sampling, compression and encryption for signal acquisition are unified under the secure multiparty computation protocol. In the proposed scheme, generation of the pseudo-random sensing matrix offers a natural method for data encryption in DCS, allowing for joint recovery of multiparty data at legal users’ side. Experimental analysis and results indicate that the secure signal processing and recovery in DCS domain is feasible, and requires fewer measurements than the achievable approach of separate CS and Nyquist processing. The proposed scheme can be also extended to other cloud-based collaborative secure signal processing and data-mining applications.
Year
DOI
Venue
2016
10.1007/s11045-015-0371-2
Multidimensional Systems and Signal Processing
Keywords
Field
DocType
Multi-sourced fusion,Secure signal processing,Distributed compressed sensing,Cloud computing,Measurement matrix
Signal processing,Mathematical optimization,Secure multi-party computation,Computer science,Fusion,Encryption,Sampling (statistics),Nyquist–Shannon sampling theorem,Computer hardware,Compressed sensing,Distributed computing,Cloud computing
Journal
Volume
Issue
ISSN
27
4
1573-0824
Citations 
PageRank 
References 
3
0.42
18
Authors
5
Name
Order
Citations
PageRank
Huimin Zhao120623.43
Wenguo Wei2211.02
Jun Cai337339.29
Fangyuan Lei440.78
Jianzhen Luo5211.70