A Perturbed Compressed Sensing Protocol for Crowd Sensing
Joint Authors
Li, Meng
Zhu, Liehuang
Zhang, Zijian
Jin, Chengcheng
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-06-13
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Telecommunications Engineering
Abstract EN
Crowd sensing network is a data-centric network consisting of many participants uploading environmental data by smart mobile devices or predeployed sensors; however, concerns about communication complexity and data confidentiality arise in real application.
Recently, Compressed Sensing (CS) is a booming theory which employs nonadaptive linear projections to reduce data quantity and then reconstructs the original signal.
Unfortunately, privacy issues induced by untrusted network still remain to be unsettled practically.
In this paper, we consider crowd sensing using CS in wireless sensor network (WSN) as the application scenario and propose a data collection protocol called perturbed compressed sensing protocol (PCSP) to preserve data confidentiality as well as its practicality.
At first, we briefly introduce the CS theory and three factors correlated with reconstruction effect.
Secondly, a secure CS-based framework using a secret disturbance is developed to protect raw data in WSN, in which each node collects, encrypts, measures, and transmits the sampled data in our protocol.
Formally, we prove that our protocol is CPA-secure on the basis of a theorem.
Finally, evaluation on real and simulative datasets shows that our protocol could not only achieve higher efficiency than related algorithms but also protect signal’s confidentiality.
American Psychological Association (APA)
Zhang, Zijian& Jin, Chengcheng& Li, Meng& Zhu, Liehuang. 2016. A Perturbed Compressed Sensing Protocol for Crowd Sensing. Mobile Information Systems،Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1111369
Modern Language Association (MLA)
Zhang, Zijian…[et al.]. A Perturbed Compressed Sensing Protocol for Crowd Sensing. Mobile Information Systems No. 2016 (2016), pp.1-9.
https://search.emarefa.net/detail/BIM-1111369
American Medical Association (AMA)
Zhang, Zijian& Jin, Chengcheng& Li, Meng& Zhu, Liehuang. A Perturbed Compressed Sensing Protocol for Crowd Sensing. Mobile Information Systems. 2016. Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1111369
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1111369