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A model for aggregation and filtering on encrypted XML streams in fog computing

Author

Listed:
  • Jyun-Yao Huang
  • Wei-Chih Hong
  • Po-Shin Tsai
  • I-En Liao

Abstract

The Internet of Things provides visions of innovative services and domain-specific applications. With the development of Internet of Things services, various structural data need to be transferred over the Internet. However, protecting structural information that contains sensitive data has raised concerns against Internet of Things services. For a publish/subscribe scenario consisting of sensors, fog nodes, and subscribers, we propose a model that (1) expands the present XML Encryption standard for data with string and numeric types implemented in the sensors, (2) efficiently and discreetly filters matched streaming data and performs summation in the fog nodes, and (3) decrypts the filtered and aggregated data in the subscribers without revealing privacy data. The experimental results of the performance on fog node implemented by PC or Raspberry Pi show that the proposed model can rapidly process multiple encrypted XML streams generated by sensors in a parallel manner without revealing privacy data to subscribers. Therefore, the proposed model is a solution to the fog computing applications in which the privacy preservation of sensor data is of great concern.

Suggested Citation

  • Jyun-Yao Huang & Wei-Chih Hong & Po-Shin Tsai & I-En Liao, 2017. "A model for aggregation and filtering on encrypted XML streams in fog computing," International Journal of Distributed Sensor Networks, , vol. 13(5), pages 15501477177, May.
    • Handle: RePEc:sae:intdis:v:13:y:2017:i:5:p:1550147717704158
    DOI: 10.1177/1550147717704158
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    References listed on IDEAS

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    1. Feng Chen & Pan Deng & Jiafu Wan & Daqiang Zhang & Athanasios V. Vasilakos & Xiaohui Rong, 2015. "Data Mining for the Internet of Things: Literature Review and Challenges," International Journal of Distributed Sensor Networks, , vol. 11(8), pages 431047-4310, August.
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