Machine Learning Techniques for Cyber Security in Internet of Robotic Things

Robots are becoming common in domestic, medical, industrial, entertainment, and educational routine activities. The use of robots automates the work processes thus minimizes human labor. The Robots perform complex and repetitive tasks with efficiency and agility, therefore, the conventional industrial manufacturing process are being replaced by smart manufacturing. Robotics encompasses the design and development of robot-based automated systems. It integrates various emerging technologies i.e. operational technology (OT), cloud computing, and artificial intelligence (AI). The Internet of Robotic Things (IoRT) seamlessly combines robots and Internet of Things (IoT) devices, enabling connectivity through the Internet. IoRT enables simple robots to coordinate with each other to achieve well-defined goals by creating a multi-robot system. Cyber security is an inherent challenge for IoRTs because of the interconnected infrastructure and reliance on critical industrial operations on the internet. Any cyber-attack can affect the ongoing operations and compromise the safety of robots. The growing interest among governments, researchers, and industries in robotics and automation demands a dependable cyber-security solution. This paper explores machine learning (ML) based cyber security solutions to mitigate cyber vulnerabilities and threats to IoRT and its dependent systems.