4.6 Article

A Reliable and Lightweight Trust Computing Mechanism for IoT Edge Devices Based on Multi-Source Feedback Information Fusion

Journal

IEEE ACCESS
Volume 6, Issue -, Pages 23626-23638

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2018.2831898

Keywords

Internet of Things; edge computing; trust computing mechanism; feedback trust; multi-source feedback information fusion; objective information entropy theory

Funding

  1. National Nature Science Foundation of China [61672111]
  2. National Key Research and Development Program of China [2016QY03D0605]
  3. Beijing Natural Science Foundation [4162043]

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The integration of Internet of Things (IoT) and edge computing is currently a new research hotspot. However, the lack of trust between IoT edge devices has hindered the universal acceptance of IoT edge computing as outsourced computing services. In order to increase the adoption of IoT edge computing applications, first, IoT edge computing architecture should establish efficient trust calculation mechanism to alleviate the concerns of numerous users. In this paper, a reliable and lightweight trust mechanism is originally proposed for IoT edge devices based on multi-source feedback information fusion. First, due to the multi-source feedback mechanism is used for global trust calculation, our trust calculation mechanism is more reliable against bad-mouthing attacks caused by malicious feedback providers. Then, we adopt lightweight trust evaluating mechanism for cooperations of IoT edge devices, which is suitable for large-scale IoT edge computing because it facilitates low-overhead trust computing algorithms. At the same time, we adopt a feedback information fusion algorithm based on objective information entropy theory, which can overcome the limitations of traditional trust schemes, whereby the trust factors are weighted manually or subjectively. And the experimental results show that the proposed trust calculation scheme significantly outperforms existing approaches in both computational efficiency and reliability.

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