Journal of Shanghai Jiaotong University (Science)

, Volume 24, Issue 1, pp 101–106 | Cite as

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

  • Lan Dai (戴澜)Email author
  • Qiangqiang Yan (闫强强)
  • Shengyu Yi (易盛禹)
  • Wenkai Liu (刘文楷)
  • He Qian (钱鹤)


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.

Key words

physical unclonable functions resistive random access memory machine learning attack antimachine learning attack XOR RRAM PUF 

CLC number

TN 79 

Document code


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Copyright information

© Shanghai Jiaotong University and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Lan Dai (戴澜)
    • 1
    Email author
  • Qiangqiang Yan (闫强强)
    • 1
  • Shengyu Yi (易盛禹)
    • 1
    • 2
  • Wenkai Liu (刘文楷)
    • 1
  • He Qian (钱鹤)
    • 2
  1. 1.Academy of Electronic Information EngineeringNorth China University of TechnologyBeijingChina
  2. 2.Institute of MicroelectronicsTsinghua UniversityBeijingChina

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