Demonstrating Danger Theory based threat detection for robotic manufacture protection

Abstract

The aid of automated guided vehicles (AGV) is indispensable for complex manufacturing processes. However, a cyber attack on an AGV or an AGV control centre can easily lead o considerable direct physical damage and further indirect costs due to disruption of manufacturing process. Previous incidents show that most damage comes from previously unseen threats, hose that cannot be prevented by detecting known attack signatures. In this demo, we show an approach to protect industrial process of robotic manufacture facilities from cyber attacks based on Artificial Immune Systems paradigm using Danger Theory.