An ETH-based approach to securing industrial Internet systems against mutinous attacks

Abstract

In modern manufacturing industries, industrial components are becoming increasingly open and interconnected which significantly promotes the collaboration capability and producing efficiency on one hand, while, on the other hand, makes the industrial internet more vulnerable to various threats and attacks. In order to defend a distributed industrial Internet network system against two kinds of typical mutinous attacks, i.e., Byzantine attacks and DDoS attacks, that happen inside of the system, this paper proposes an Ethereum-based securing strategy. First, a credit mechanism-based Bayesian inference method is developed to increase the system nodes' sensitivity to malicious behavior and to improve system's robustness against false messages. Then, a miner selection method is proposed to avoid the information clog occurring in the system nodes' txpools and improve the efficiency of the whole system. The constructed securing strategy consists of these two methods and is shown to be applicable to industrial scenarios involving both mobile and static nodes. Several simulations are presented to verify effectiveness of the proposed approach. It is found that the accuracy of identifying false messages broadcast by Byzantine attackers is about 90%.