A Self-Oscillated Organic Synapse for In-Memory Two-Factor Authentication.

Journal: Advanced science (Weinheim, Baden-Wurttemberg, Germany)
PMID: 38520711

Abstract

Entering the era of AI 2.0, bio-inspired target recognition facilitates life. However, target recognition may suffer from some risks when the target is hijacked. Therefore, it is significantly important to provide an encryption process prior to neuromorphic computing. In this work, enlightened from time-varied synaptic rule, an in-memory asymmetric encryption as pre-authentication is utilized with subsequent convolutional neural network (ConvNet) for target recognition, achieving in-memory two-factor authentication (IM-2FA). The unipolar self-oscillated synaptic behavior is adopted to function as in-memory asymmetric encryption, which can greatly decrease the complexity of the peripheral circuit compared to bipolar stimulation. Results show that without passing the encryption process with suitable weights at the correct time, the ConvNet for target recognition will not work properly with an extremely low accuracy lower than 0.86%, thus effectively blocking out the potential risks of involuntary access. When a set of correct weights is evolved at a suitable time, a recognition rate as high as 99.82% can be implemented for target recognition, which verifies the effectiveness of the IM-2FA strategy.

Authors

  • Shuzhi Liu
    Division of Electronics and Electrical Engineering, Dongguk University-Seoul, Seoul 04620, Korea.
  • Xiaolong Zhong
    Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
  • Yuxuan Li
    Department of Biomedical Informatics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, 100191, China.
  • Bingjie Guo
    School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
  • Zhilong He
    Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, College of Electronic and Information Engineering, Southwest University, Chongqing, 400715, PR China.
  • Zhixin Wu
    Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
  • Sixian Liu
    Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
  • Yanbo Guo
    McMaster Children's Hospital, McMaster University, Hamilton, Ontario, Canada.
  • Xiaoling Shi
    Department of Otolaryngology, Shanghai Key Clinical Disciplines of Otorhinolaryngology, Eye Ear Nose & Throat Hospital, Fudan University, Shanghai, PR China.
  • Weilin Chen
    Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
  • Hongxiao Duan
    Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
  • Jianmin Zeng
    Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
  • Gang Liu
    Department of Interventional Radiology, Qinghai Red Cross Hospital, Xining, Qinghai, China.

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