Secure Calibration for Safety-Critical IoT: Traceability for Safety Resilience
This addresses the safety and security vulnerabilities in IoT calibration infrastructure, which is critical for industrial applications, representing a novel approach to a known bottleneck.
The paper tackles the problem of insecure and inefficient manual calibration in safety-critical IoT by proposing a resilient architecture using Ethereum smart contracts, enabling on-the-fly verification with authentication and non-repudiation.
Secure sensor calibration constitutes a foundational step that underpins operational safety in the Industrial Internet of Things. While much attention has been given to IoT security such as the use of TLS to secure sensed data, little thought has been given to securing the calibration infrastructure itself. Currently traceability is achieved via manual verification using paper-based datasheets which is both time consuming and insecure. For instance, when the calibration status of parent devices is revoked as mistakes or mischance is detected, calibrated devices are not updated until the next calibration cycle, leaving much of the calibration parameters invalid. Aside from error, any party within the calibration infrastructure can maliciously introduce errors since the current paper based system lacks authentication as well as non-repudiation. In this paper, we propose a novel resilient architecture for calibration infrastructure, where the calibration status of sensor elements can be verified on-the-fly to the root of trust preserving the properties of authentication and non-repudiation. We propose an implementation based on smart contracts on the Ethereum network. Our evaluation shows that Ethereum is likely to address the protection requirements of traceable measurements.