Distributed compressed sensing for multi-sourced fusion and secure signal processing in private cloud

被引：3
|
作者：
Zhao, Huimin [1 ]
Wei, Wenguo [1 ]
Cai, Jun [1 ]
Lei, Fangyuan [1 ]
Luo, Jianzhen [1 ]
机构：
[1] Guangdong Polytech Normal Univ, Sch Elect & Informat, Guangzhou, Guangdong, Peoples R China
来源：
MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING | 2016年 / 27卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Multi-sourced fusion; Secure signal processing; Distributed compressed sensing; Cloud computing; Measurement matrix; LIFTING WAVELET TRANSFORM; OBJECT DETECTION; RECONSTRUCTION; ROBUSTNESS;
D O I：
10.1007/s11045-015-0371-2
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
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.
引用
收藏
页码：891 / 908
页数：18
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