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Privacy-Preserving and Traceable Data Aggregation in Energy Internet

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Mobile Ad-hoc and Sensor Networks (MSN 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 747))

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Abstract

Energy Internet is considered as a promising approach to solve the problems of energy crisis and carbon emission. It needs to collect user’s real-time data for optimizing the energy utilization. Edge nodes like GWs (gateway) are used for data aggregation to improve the efficiency of the system. Due to a large number of GWs are widely distributed and difficult to be managed, which brings potential security threats for the Energy Internet. Existing data aggregation schemes fails in preventing the adversary from controlling or destroying GWs. In this paper, we propose an IBE-based Device Traceable Privacy-Preserving Aggregation Scheme, named IBE-DTPPA. Increasing the RA (Residential Area) users’ data aggregation integrity verification by BGN Cryptosystem; using IBE Cryptosystem to encrypt aggregation data, calculating ciphertext based on GW’s dynamic ID, realizing the target GW traceability; choosing CC (Control Center) dynamic identity information as public key to realize CC authentication, preventing adversary from using CC’s identity fraudulently. Through extensive analysis, we demonstrate that IBE-DTPPA resists various security threats, and can trace target GW efficiently.

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Acknowledgement

This work is partially supported by Natural Science Foundation of China under grant 61402171, the Fundamental Research Funds for the Central Universities under grant 2016MS29.

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Authors and Affiliations

  1. North China Electric Power University, Beijing, 102206, China

    Yue Zhang & Zhitao Guan

Authors
  1. Yue Zhang
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  2. Zhitao Guan
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Correspondence to Zhitao Guan .

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Editors and Affiliations

  1. Beijing Institute of Technology, Beijing, China

    Liehuang Zhu

  2. Nanjing University, Nanjing, China

    Sheng Zhong

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Zhang, Y., Guan, Z. (2018). Privacy-Preserving and Traceable Data Aggregation in Energy Internet. In: Zhu, L., Zhong, S. (eds) Mobile Ad-hoc and Sensor Networks. MSN 2017. Communications in Computer and Information Science, vol 747. Springer, Singapore. https://doi.org/10.1007/978-981-10-8890-2_33

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  • DOI: https://doi.org/10.1007/978-981-10-8890-2_33

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8889-6

  • Online ISBN: 978-981-10-8890-2

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