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Energy-Saving and Efficient Underwater Wireless Sensor Network Security Data Aggregation Model

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The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIOT 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1283))

Abstract

Due to the inherent characteristics of resource constrained sensors, communication overhead has always been a major problem in underwater wireless sensor networks. Data aggregation is an important technology to reduce communication overhead and prolong network lifetime. In addition, due to the low bandwidth and high bit error rate transmission characteristics of underwater wireless media, underwater sensor nodes are more vulnerable to malicious attacks. Therefore, for such applications, data aggregation protocol must be energy-saving and efficient, and can prevent adversaries from stealing private data held by each sensor node. To solve this problem, this paper proposes an improved Energy-efficient Slice-Mix-Aggregate (ESMART) algorithm, which dynamically adjusts the number of data slices according to the amount of data sensed by the sensor nodes, which makes the total data transmission volume in the network lower than that of SMART (Slice-Mix-Aggregate) algorithm, that is, it does not introduce significant overhead on the sensor with limited energy, while maintaining the data security.

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Acknowledgment

This work was supported by the following projects: the National Natural Science Foundation of China (61862020); the key research and development project of Hainan Province (ZDYF2018006); Hainan University-Tianjin University Collaborative Innovation Foundation Project (HDTDU202005).

Author information

Authors and Affiliations

  1. Information and Communication Engineering of Hainan University, Haikou, 570228, China

    Shijie Sun

  2. Computer Science and Cyberspace Security of Hainan University, Haikou, 570228, China

    Shijie Sun, Dandan Chen, Na Liu, Xiangdang Huang & Qiuling Yang

  3. State Key Laboratory of Marine Resource Utilization in South China Sea, Haikou, 570228, China

    Xiangdang Huang & Qiuling Yang

Authors
  1. Shijie Sun
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  2. Dandan Chen
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  3. Na Liu
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  4. Xiangdang Huang
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  5. Qiuling Yang
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Corresponding author

Correspondence to Xiangdang Huang .

Editor information

Editors and Affiliations

  1. David Goldman Informatics Centre, University of Sunderland, Sunderland, UK

    John MacIntyre

  2. University of Shanghai for Science and Technology, Shanghai, China

    Jinghua Zhao

  3. Shenzhen University, Shenzen, Guangdong, China

    Xiaomeng Ma

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© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG

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Sun, S., Chen, D., Liu, N., Huang, X., Yang, Q. (2021). Energy-Saving and Efficient Underwater Wireless Sensor Network Security Data Aggregation Model. In: MacIntyre, J., Zhao, J., Ma, X. (eds) The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy. SPIOT 2020. Advances in Intelligent Systems and Computing, vol 1283. Springer, Cham. https://doi.org/10.1007/978-3-030-62746-1_31

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