A lightweight and anti‐collusion trust model combined with nodes dynamic relevance for the power internet of things

Author:

Zhao Shice1ORCID,Zhao Hongshan1,Sun Jingjie2

Affiliation:

1. School of Electrical and Electronic Engineering North China Electric Power University Baoding China

2. Economic and Technological Research Institute of State Grid Shannxi Electric Power Co., Ltd Xi'an China

Abstract

AbstractA large number of monitoring sensors are introduced in the power grid. However, the traditional trust models commonly used for edge‐side security management are weak in detecting large‐scale malicious interactions and collusion attacks. For that, a lightweight and anti‐collusion trust model combined with nodes’ dynamic relevance for the power Internet of Things (IoT) is proposed. Firstly, a global trust management system is constructed according to the working mechanism of sensors in the power grid. After that, trust feedback and contact frequency of the devices are combined to build an adaptive dynamic weight vector based on relevance volatility. Fluctuations in trust values are reduced and the trust difference between normal and malicious nodes is widened. An anti‐collusion algorithm based on contact set awareness is also designed to effectively detect collusion attacks. The checksum local broadcast is established in the trust model to counteract the risk of intelligent terminal failure. The results show that the trust model achieves 100% accuracy of node discrimination when the maximum proportion of malicious nodes is 20% in a 50‐node network scale. In addition, the calculation time of the overall model is 211 ms and the memory consumption is 161 kb, which is suitable for power IoT sensor networks.

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics

Reference34 articles.

1. IoT-based optimal demand side management and control scheme for smart microgrid

2. Reliability confidence interval prediction for communication link of wireless sensor network in smart grid;Sun W.;Autom. Electr. Power Syst,2017

3. Survey on synchrophasor data quality and cybersecurity challenges, and evaluation of their interdependencies

4. A Fast Abnormal Data Cleaning Algorithm for Performance Evaluation of Wind Turbine

5. Research on power grid security protection archi‐tecture based on zero trust;Liu T.;Int. Conf. Electr. Eng. Inform. Commun. Technol.,2021

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