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Low-cost and confidentiality-preserving data acquisition for Internet of Multimedia Things
journal contribution
posted on 2018-10-01, 00:00 authored by Yushu Zhang, Q He, Yong XiangYong Xiang, Leo ZhangLeo Zhang, Bo Liu, J Chen, Y XieIEEE Internet of Multimedia Things (IoMT) faces the challenge of how to realize low-cost data acquisition while still preserve data confidentiality. In this work, we present a low-cost and confidentiality-preserving data acquisition framework for IoMT. Firstly, we harness chaotic convolution and random subsampling to capture multiple image signals. The measurement matrix is under the control of chaos, ensuring the security of the sampling process. Next, we assemble these sampled images into a big master image, and then encrypt this master image based on Arnold transform and single value diffusion. The computation of these two transforms only requires some low-complexity operations. Finally, the encrypted image is delivered to cloud servers for storage and decryption service. Experimental results demonstrate the security and effectiveness of the proposed framework.
History
Journal
IEEE Internet of things journalVolume
5Issue
5Pagination
3442 - 3451Publisher
Institute of Electrical and Electronics EngineersLocation
Piscataway, N.J.Publisher DOI
eISSN
2327-4662Language
engPublication classification
C Journal article; C1 Refereed article in a scholarly journalCopyright notice
2017, IEEEUsage metrics
Categories
Keywords
compressive sensingchaotic encryptionbig image dataInternet of Multimedia ThingsScience & TechnologyTechnologyComputer Science, Information SystemsEngineering, Electrical & ElectronicTelecommunicationsComputer ScienceEngineeringcompressive sensing (CS)Internet of Multimedia Things (IoMT)FRACTIONAL MELLIN TRANSFORMEFFICIENT IMAGE ENCRYPTIONDATA AGGREGATIONCHAOTIC SYSTEMMAPRECONSTRUCTIONCOMPRESSIONDIFFUSIONSECUREInformation SystemsDistributed Computing
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