@inproceedings{ErozanAghassiHagmannTahoori2019, author = {Ahmet Turan Erozan and Jasmin Aghassi-Hagmann and Mehdi Baradaran Tahoori}, title = {Inkjet Printed True Random Number Generator based on Additive Resistor Tuning}, series = {Proceedings of the 2019 Design, Automation \& Test in Europe (DATE)}, publisher = {IEEE}, isbn = {978-3-9819263-2-3 (Online)}, issn = {1558-1101 (Online)}, doi = {10.23919/DATE.2019.8715071}, pages = {1361 -- 1366}, year = {2019}, abstract = {Printed electronics (PE) is a fast growing technology with promising applications in wearables, smart sensors and smart cards since it provides mechanical flexibility, low-cost, on-demand and customizable fabrication. To secure the operation of these applications, True Random Number Generators (TRNGs) are required to generate unpredictable bits for cryptographic functions and padding. However, since the additive fabrication process of PE circuits results in high intrinsic variation due to the random dispersion of the printed inks on the substrate, constructing a printed TRNG is challenging. In this paper, we exploit the additive customizable fabrication feature of inkjet printing to design a TRNG based on electrolyte-gated field effect transistors (EGFETs). The proposed memory-based TRNG circuit can operate at low voltages (≤ 1 V ), it is hence suitable for low-power applications. We also propose a flow which tunes the printed resistors of the TRNG circuit to mitigate the overall process variation of the TRNG so that the generated bits are mostly based on the random noise in the circuit, providing a true random behaviour. The results show that the overall process variation of the TRNGs is mitigated by 110 times, and the simulated TRNGs pass the National Institute of Standards and Technology Statistical Test Suite.}, language = {en} }