Detection of Security Attacks in Industrial IoT Networks: A Blockchain and Machine Learning Approach

Electronics

Henry Vargas¹  Germán A. Montoya¹  Carlos Lozano-Garzon¹  Yezid Donoso¹ 

[1] Systems and Computing Engineering Department, Universidad de Los Andes, Bogotá 111711, Colombia;

关键词: blockchain;    Industrial Internet of Things (IIoT);    intrusion;    machine learning;   

DOI  :  10.3390/electronics10212662

来源: DOAJ

【 摘 要 】

Internet of Things (IoT) networks have been integrated into industrial infrastructure schemes, positioning themselves as devices that communicate highly classified information for the most critical companies of world nations. Currently, and in order to look for alternatives to mitigate this risk, solutions based on Blockchain algorithms and Machine Learning techniques have been implemented separately with the aim of mitigating potential threats in IIoT networks. In this paper, we sought to integrate the previous solutions to create an integral protection mechanism for IoT device networks, which would allow the identification of threats, activate secure information transfer mechanisms, and it would be adapted to the computational capabilities of industrial IoT. The proposed solution achieved the proposed objectives and is presented as a viable mechanism for detecting and containing intruders in an IoT network. In some cases, it overcomes traditional detection mechanisms such as an IDS.

【 授权许可】

Unknown