Article

Low-Cost and Confidentiality-Preserving Data Acquisition for Internet of Multimedia Things

Yushu ZhangChongqing University Key Laboratory of Networks and Cloud Computing Security, School of Electronics and Information Engineering, Southwest University, Chongqing, ChinaQi HeChongqing University Key Laboratory of Networks and Cloud Computing Security, School of Electronics and Information Engineering, Southwest University, Chongqing, ChinaYong XiangSchool of Information Technology, Deakin University, AustraliaLeo Yu ZhangSchool of Information Technology, Deakin University, AustraliaBo LiuDepartment of Engineering, La Trobe University, Melbourne, VIC, AustraliaJunxin ChenSino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, ChinaYiyuan XieChongqing University Key Laboratory of Networks and Cloud Computing Security, School of Electronics and Information Engineering, Southwest University, Chongqing, China

2017en

ABI

Abstract

Internet of Multimedia Things (IoMT) faces the challenge of how to realize low-cost data acquisition while still preserve data confidentiality. In this paper, we present a low-cost and confidentiality-preserving data acquisition framework for IoMT. First, 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.

Identifiers

DOI: 10.1109/jiot.2017.2781737

Citations and references

Cited by 20 references

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