Witness Box Protocol: Automatic machine identification and authentication in industry 4.0

Abstract

The current wave of Industrial Internet of Things (IIoT) is reshaping the manufacturing sector with system interoperability, remote real-time process monitoring and advanced analytics. As digitally enabled manufacturing machines continue to grow exponentially, it becomes imperative to uniquely and securely identify them in the cyber-physical world, particularly in defense, biomedical, energy and aerospace manufacturing. Research about threats originating from internal adversaries’ i.e the machine/organization owner within a tiered digitally connected supply chain is scarce. This paper introduces a machine fingerprinting scheme named as the ‘Witness Box Protocol’ (WBP) that exploits the physical properties of manufacturing machines (legacy or smart) and their surroundings to create a unique biometric like fingerprint. WBP provides both machine registration and authentication on a digital network through a low cost, non-invasive approach. The fingerprint is generated by a Locality Sensitive Hashing (LSH) technique that accommodates small variations in physical signature data and can corroborate data provenance from machines by verifying machine identity through authentication. Additionally, this fingerprint hash simplifies asset management within a large enterprise or distributed network comprising of thousands of machines in a Manufacturing-as-a-Service (MaaS) paradigm. In this research, fingerprints were randomly generated from the statistical features of signals from 3D printers and CNC machine in a production-like lab environment. Using k-means clustering and Jaccard similarity index, these fingerprints are shown to identify the source equipment with 95 % accuracy.