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Efficient and privacy-preserving range-max query in fog-based agricultural IoT

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Abstract

Smart agriculture Internet of Things (IoT) is a typical application of IoT and has become popular due to its advantages in automatic irrigation and fertilization, crop growth monitoring, pest and disease detection, etc. To reduce resource waste, minimize environmental impact, and maximize crop yield, most smart agricultural applications require to collect and process agricultural data in real-time. However, the computational and storage resources of the agricultural IoT devices are limited. To alleviate the computational and storage pressure on agriculture IoT devices and timely process the collected data collected by IoT devices, the fog node is usually placed at the edge of the agricultural IoT. Nevertheless, the fog node may not be completely trusted. The agricultural IoT devices’ data stored in the fog node will face the potential risk of privacy leakage. In this paper, to preserve the privacy of agricultural IoT devices’ data and user query’s result in the fog-based smart agriculture IoT, we first build the K2-treap, which is used for storing the data collected by agriculture IoT devices and support efficient range-max query and dynamic update of the data. Then, we design a data encryption and comparison algorithm based on BGN homomorphic encryption technique and present an efficient and privacy-preserving range-max query in the fog-based smart agriculture IoT, which can not only securely compare two data based on their ciphertexts but also support the incremental update directly over ciphertexts. Notably, our comparison technique and range-max queries are run by the fog node, so there are no interactions between the agricultural IoT devices and the fog node during the comparison and query. Finally, we conduct a detailed security analysis and performance evaluation. The results show that our proposed scheme can indeed protect the privacy of the agricultural IoT devices’ data and query results, and the experimental test results prove that our proposed scheme is efficient.

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Acknowledgements

This work was supported by the China Scholarship Council when Min Zhou was visiting the University of New Brunswick, Canada. This work was also supported in part by the National Natural Science Foundation of China (No. 61872152, 61872409, 61902132), the Natural Science Foundation of Guangdong Province (No. 2018A03 0310147), Guangdong Basic and Applied Basic Research Foundation (No. 2019B030302008, No. 2020A1515010751), Science and Technology Program of Guangzhou (No.201902010081), Guangzhou Key Laboratory of Intelligent Agriculture.

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Authors and Affiliations

  1. College of Mathematics and Informatics, South China Agriculture University, Guangzhou, 510642, China

    Min Zhou & Limin Peng

  2. Faculty of Computer Science, University of New Brunswick, Fredericton, NB, E3B 5A3, Canada

    Min Zhou, Yandong Zheng, Yunguo Guan & Rongxing Lu

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  1. Min Zhou
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  2. Yandong Zheng
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Correspondence to Min Zhou.

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Zhou, M., Zheng, Y., Guan, Y. et al. Efficient and privacy-preserving range-max query in fog-based agricultural IoT. Peer-to-Peer Netw. Appl. 14, 2156–2170 (2021). https://doi.org/10.1007/s12083-021-01179-2

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