A Novel RRAM Based PUF for Anti-Machine Learning Attack and High Reliability

• Published in: Shanghai jiao tong da xue xue bao 2019-02, Vol.24 (1), p.101-106
• Main Authors: Dai, Lan, Yan, Qiangqiang, Yi, Shengyu, Liu, Wenkai, Qian, He
• Format: Article
• Language: English
• Subjects: Aging; Architecture; Artificial intelligence; Baking; Computer Science; Current distribution; Dependence; Electrical Engineering; Engineering; Filaments; High temperature; Learning algorithms; Life Sciences; Machine learning; Materials Science; Random access memory; Reliability; Security; Stability; Thermal resistance
• ISSN: 1007-1172; 1674-8115; 1995-8188
• DOI: 10.1007/s12204-019-2043-0

Due to the unique response mechanism, physical unclonable function (PUF) has been extensively studied as a hardware security primitive. And compared to other PUFs, the resistive random access memory (RRAM) based PUF has more flexibility with the change of conductive filaments. In this work, we propose an exclusive or (XOR) strong PUF based on the 1 Kbit 1-transistor-1-resistor (1T1R) arrays, and unlike the traditional RRAM based strong PUF, the XOR PUF has a stronger anti-machine learning attack ability in our experiments. The reliability of XOR RRAM PUF is determined by the read instability, thermal dependence of RRAM resistance, and aging. We used a split current distribution scheme to make the reliability of XOR PUF significantly improved. After baking for 50 h at a high temperature of 150°C, the intra-chip Hamming distance (Intra-HD) only increased from 0 to 4.5%. The inter-chip Hamming distance (Inter-HD) and uniformity are close to 50% (ideally). And it is proven through the NIST test that XOR PUF has a high uniqueness.