Taxonomies for Reasoning About Cyber-physical Attacks in IoT-based Manufacturing Systems

The Internet of Things (IoT) has transformed many aspects of modern manufacturing, from design to production to quality inspection. In particular, IoT and digital manufacturing technol-ogies have substantially accelerated product development-cycles and manufacturers can now create products of a complexity and precision not heretofore possible. However, new threats to supply chain security have arisen from connecting machines to the In-ternet and introducing complex IoT-based systems controlling manufacturing processes. By attacking these IoT-based manu-facturing systems and tampering with digital files, attackers can manipulate physical characteristics of parts and change the dimensions, shapes, or mechanical properties of the parts, which can result in parts that fail in the field. These defects increase manufacturing costs and allow silent problems to occur only under certain loads that can threaten safety and/or lives. To under-stand potential dangers and protect manufacturing system integrity, this paper presents two taxonomies: one for classifying cyber-physical attacks against manufacturing processes and another for quality inspection measures for counteracting these attacks. We systematically identify and classify possible cyberphysical attacks and connect the attacks with variations in manufacturing processes and quality inspection measures. Our taxonomies also provide a scheme for linking emerging IoT-based manufacturing system vulnerabilities to possible attacks and quality inspection measures.