A PUF sensor: Securing physical measurements
Date
2017
Authors
Ma, H.
Gao, Y.
Kavehei, O.
Ranasinghe, D.
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Conference paper
Citation
Proceedings of the IEEE International Conference on Pervasive Computing and Communications (PerCom 2017), 2017, pp.648-653
Statement of Responsibility
Hua May, Yansong Gaoy, Omid Kaveheiz, and Damith C. Ranasinghe
Conference Name
IEEE International Conference on Pervasive Computing and Communications (PerCom 2017) (13 Mar 2017 - 17 Mar 2017 : Kona, Hawaii)
Abstract
Sensors are important components in the Internet of Things (IoT) that encompass a wide spectrum of applications from healthcare to monitoring critical infrastructure. Securely gathering sensor measurements by adopting traditional cryptographic mechanisms is fraught with vulnerabilities emanating from the inability to safeguard secrets on edge devices, often in adversarial environments, where appropriate hardware protection logic and power consumption overheads are counterproductive to the desire to keep the devices low cost and long lasting. This paper continues recent efforts into investigating an alternative secure sensing approach with the potential to provide a solution for resource-restricted IoT devices. In particular, we investigate the possibility to exploit unreliability of a physical unclonable function (PUF) resulting from its sensitivity to variations in supply voltage conditions to guarantee the veracity of physical measurements from potentially any transducer capable of converting a physical phenomenon to a voltage signal. Therefore we present an approach that has the potential to realize a universal PUF sensor where the PUF itself acts as a sensor or is integrated with a sensor. Thus, for a PUF sensor, cryptographic processes and sensing are inseparable. Further, we rely on a dominant external condition—voltage—responsible for unreliability to secure sensing. We validate the feasibility of the proposed universal PUF sensor approach based on experimental data extracted from RO-PUFs (Ring Oscillator PUFs).
School/Discipline
Dissertation Note
Provenance
Description
2nd IEEE PERCOM Workshop On Security Privacy And Trust In The Internet of Things 2017
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© 2017 IEEE