Secure Calibration for Safety-Critical IoT: Traceability for Safety Resilience
Ryan Shah, Michael McIntee, Shishir Nagaraja, Sahil Bhandary, Prerna, Arote, Joy Kuri

TL;DR
This paper introduces a blockchain-based architecture for secure, traceable sensor calibration in IoT, enhancing safety and integrity by enabling real-time verification and preventing malicious errors.
Contribution
It presents a novel resilient calibration infrastructure using Ethereum smart contracts to ensure secure, tamper-proof traceability and real-time verification of calibration status.
Findings
Ethereum can effectively support secure traceability in calibration.
The proposed system improves security over paper-based methods.
Real-time verification enhances safety in IoT environments.
Abstract
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…
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Taxonomy
TopicsPhysical Unclonable Functions (PUFs) and Hardware Security · IoT and Edge/Fog Computing · Blockchain Technology Applications and Security
