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Internet of Things Security

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Secure Compressive Sensing in Multimedia Data, Cloud Computing and IoT

Part of the book series: SpringerBriefs in Electrical and Computer Engineering ((BRIEFSSIGNAL))

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Abstract

The CS’s advantage of low-energy sampling makes it be well used for IoT with limited resources. Besides of energy consideration, this chapter focuses mainly on the security aspects. A low-cost and confidentiality-preserving data acquisition framework in IoT based on chaotic convolution and random subsampling is firstly proposed. Chaotic encryption ensures the security of sampling process. The sampled images are assembled into a big master image, which is encrypted by Arnold transform and single value diffusion. Both of these two encryption operations both have low computational complexity. The final encrypted image is uploaded to cloud servers for storage and decryption service. Then, we discussed the issue of how to securely store and share these big image data from IoT. We harness the hybrid cloud to provide secure big image data storage and share service for users. The basic idea is to partition each image into a small set of sensitive data and a large set of insensitive data, which are securely stored in the private cloud and the public cloud, respectively.

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Authors and Affiliations

  1. School of Information Technology, Deakin University, Burwood, Melbourne, VIC, Australia

    Yushu Zhang, Yong Xiang & Leo Yu Zhang

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  1. Yushu Zhang
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  2. Yong Xiang
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  3. Leo Yu Zhang
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Correspondence to Yushu Zhang .

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© 2019 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Zhang, Y., Xiang, Y., Zhang, L.Y. (2019). Internet of Things Security. In: Secure Compressive Sensing in Multimedia Data, Cloud Computing and IoT. SpringerBriefs in Electrical and Computer Engineering(). Springer, Singapore. https://doi.org/10.1007/978-981-13-2523-6_5

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  • DOI: https://doi.org/10.1007/978-981-13-2523-6_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-2522-9

  • Online ISBN: 978-981-13-2523-6

  • eBook Packages: EngineeringEngineering (R0)

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