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A data compression and encryption method for green edge computing

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Abstract

Green edge computing aims to reasonably allocate computing resources on the premise of ensuring the reliability of information services. The computing power gap between terminal and edge server makes the traditional encryption algorithm waste too much energy when dealing with massive redundant data. How to improve encryption efficiency and reduce the computing consumption of massive data terminal equipment on the premise of ensuring data security is one of the goals of green edge computing. We proposed a data compression and encryption scheme based on compression sensing, which greatly reduces the computing consumption of computing limited data terminals; At the same time, the hyper chaotic system is used to further encrypt the data by Arnold transform, bitwise XOR and data random scrambling. In order to solve the problem that compressed sensing can not accurately recover data, we designed a nonlinear encryption scheme based on Chinese Remainder Theorem as a supplement. The simulation results show that the proposed data compression and encryption method is effective and reliable, which has high security performance, compression ability for text data and images, and high recovery ability when the compression ratio is more than 0.5.

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Images “Lena”, “peppers” and “Lake” are obtained through Google. The meteorological data are available in http://data.cma.cn/Market/Detail/code/A.0012.0001/type/0.html.

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Funding

This work was supported National Natural Science Foundation of China (61971014, 11675199) and Young Backbone Teacher Training Program of Henan Colleges and Universities (2021GGJS170).

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Authors and Affiliations

  1. Computer Center, The Institute of High Energy Physics of the Chinese Academy of Sciences, Beijing, 100049, China

    Jianli Liu

  2. Faculty of information Technology, Beijing University of Technology, Beijing, 100124, China

    Jianli Liu, Yu Zhang & Bei Gong

  3. School of Information Science and Technology, Zhengzhou Normal University, Zhengzhou, 450044, China

    Yu Zhang

Authors
  1. Jianli Liu
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  2. Yu Zhang
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  3. Bei Gong
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Contributions

All authors contributed to the study’s conception and design. (1) JL: Conceptualization, methodology, software, data curation, writing—original draft, writing—review and editing; (2) YZ: Validation, investigation, resources, writing, visualization, funding acquisition. (3) BG: Methodology, formal analysis, review & editing, supervision, project administration, and funding acquisition.

Corresponding author

Correspondence to Bei Gong.

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Liu, J., Zhang, Y. & Gong, B. A data compression and encryption method for green edge computing. Cluster Comput 26, 3341–3359 (2023). https://doi.org/10.1007/s10586-023-03968-1

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  • DOI: https://doi.org/10.1007/s10586-023-03968-1

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