Identification of Hardware Devices based on Sensors and Switching Activity: A Preliminary Study
Honorio Martin1, Elena-Ioana Vatajelu2 and Giorgio Di Natale2
1University Carlos III of Madrid, Madrid, Spain
2Univ. Grenoble Alpes, CNRS, Grenoble INP*, TIMA, 38000 Grenoble, France
ABSTRACT
Hardware device identification has become an important feature for enhancing the security and the trust of interconnected objects. In this paper, we present a device identification method based on measuring physical and electrical properties of the device, while controlling its switching activity. The method is general an applicable to a large range of devices from FPGAs to processors, as long as they embed sensors (such as temperature and voltage) and their measurements are available. The method is enabled by the fact that both the sensors and the effects of the switching activity on the circuit are uniquely affected by manufacturing-induced process variability. The device identification based on this method is made possible by the use of machine learning. The efficiency of the method has been evaluated by a preliminary study conducted on eleven FPGAs.
Keywords: Device Fingerprinting, On-Chip Sensors, Switching Activity, Ring-Oscillator, FPGA, Neural Network.
