02244nas a2200265   4500000000100000000000100001008004100002260001200043653002600055653002300081653001800104100001200122700001600134700002000150700002000170700001600190700001800206700002500224245009300249856009800342300001000440490000600450520150800456022001401964       2017                            d  c03/201710aComputer aided design10aInternet of things10aCybersecurity1 aYao Pan1 aJules White1 aDouglas Schmidt1 aAhmad Elhabashy1 aLogan Sturm1 aJaime Camelio1 aChristopher Williams00aTaxonomies for Reasoning About Cyber-physical Attacks in IoT-based Manufacturing Systems  uhttp://www.ijimai.org/journal/sites/default/files/files/2016/08/ijimai20174_3_7_pdf_53997.pdf  a45-540 v43 aThe Internet of Things (IoT) has transformed many aspects of modern manufacturing, from design to production to quality control. In particular, IoT and digital manufacturing technologies have substantially accelerated product development- cycles and manufacturers can now create products of a complexity and precision not heretofore possible. New threats to supply chain security have arisen from connecting machines to the Internet and introducing complex IoT-based systems controlling manufacturing processes. By attacking these IoT-based manufacturing 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 understand potential dangers and protect manufacturing system safety, this paper presents two taxonomies: one for classifying cyber-physical attacks against manufacturing processes and another for quality control measures for counteracting these attacks. We systematically identify and classify possible cyber-physical attacks and connect the attacks with variations in manufacturing processes and quality control measures. Our taxonomies also provide a scheme for linking emerging IoT-based manufacturing system vulnerabilities to possible attacks and quality control measures.  a1989-1660