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A Unified PUF and TRNG Design Based on 40-nm RRAM With High Entropy and Robustness for IoT Security

Bin Gao, Bohan Lin, Xueqi Li, Jianshi Tang, He Qian, Huaqiang Wu

2022IEEE Transactions on Electron Devices62 citationsDOI

Abstract

Physically unclonable function (PUF) and true random number generator (TRNG) are the indispensable primitives for the Internet-of-Things (IoT) security. In this article, a highly robust unified PUF<inline-formula> <tex-math notation="LaTeX">$/$ </tex-math></inline-formula>TRNG design is demonstrated. An entropy source (ES) chip based on 40-nm resistive random access memory (RRAM) is designed and fabricated, and a pseudo-forming technique is developed to ensure excellent robustness. The unified PUF<inline-formula> <tex-math notation="LaTeX">$/$ </tex-math></inline-formula>TRNG is tested across <inline-formula> <tex-math notation="LaTeX">$- 55\,\,^{\circ }\text{C}$ </tex-math></inline-formula> to 125 &#x00B0;C with different supply voltages, achieving &#x003C; 0.001&#x0025; bit error rate (BER) and &#x003E;0.999 worst case min-entropy simultaneously. Excellent randomness is verified by NIST SP800-22 and 90B tests. This highly robust unified design can implement an authentication system with the authentication error rate (AER) approaching 0&#x0025; and thus is promising for future IoT security applications.

Topics & Concepts

Robustness (evolution)Resistive random-access memoryInternet of ThingsNISTPhysical unclonable functionComputer scienceNotationRandomnessEntropy (arrow of time)Random number generationTheoretical computer scienceAlgorithmCryptographyComputer engineeringEmbedded systemVoltageMathematicsElectrical engineeringEngineeringPhysicsArithmeticGeneStatisticsBiochemistryNatural language processingChemistryQuantum mechanicsPhysical Unclonable Functions (PUFs) and Hardware SecurityAdvanced Memory and Neural ComputingNeuroscience and Neural Engineering