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Distributed compressed sensing for multi-sourced fusion and secure signal processing in private cloud
- Source :
- Multidimensional Systems and Signal Processing. 27:891-908
- Publication Year :
- 2015
- Publisher :
- Springer Science and Business Media LLC, 2015.
-
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.
- Subjects :
- Signal processing
business.industry
Computer science
Applied Mathematics
Distributed computing
020206 networking & telecommunications
Cloud computing
02 engineering and technology
Encryption
Computer Science Applications
Compressed sensing
Sampling (signal processing)
Artificial Intelligence
Hardware and Architecture
Signal Processing
0202 electrical engineering, electronic engineering, information engineering
Secure multi-party computation
Nyquist–Shannon sampling theorem
020201 artificial intelligence & image processing
business
Protocol (object-oriented programming)
Software
Computer hardware
Information Systems
Subjects
Details
- ISSN :
- 15730824 and 09236082
- Volume :
- 27
- Database :
- OpenAIRE
- Journal :
- Multidimensional Systems and Signal Processing
- Accession number :
- edsair.doi...........dec719ab878885a01d1c25127f13ba7d