Bi2O2Se-Based True Random Number Generator for Security Applications

Bo Liu; Ying-Feng Chang; Juzhe Li; Xu Liu; Le An Wang; Dharmendra Verma; Hanyuan Liang; Hui Zhu; Yudi Zhao; Lain-Jong Li; Tuo-Hung Hou; Chao-Sung Lai

doi:10.1021/acsnano.2c01784

Bi₂O₂Se-Based True Random Number Generator for Security Applications

ACS Nano. 2022 Apr 26;16(4):6847-6857. doi: 10.1021/acsnano.2c01784. Epub 2022 Mar 25.

Authors

Bo Liu¹, Ying-Feng Chang², Juzhe Li¹, Xu Liu¹, Le An Wang¹, Dharmendra Verma³, Hanyuan Liang⁴, Hui Zhu¹, Yudi Zhao⁵, Lain-Jong Li⁶, Tuo-Hung Hou⁷, Chao-Sung Lai^{2

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Affiliations

¹ Faculty of Information Technology, College of Microelectronics, Beijing University of Technology, Beijing 100124, People's Republic of China.
² Artificial Intelligence Research Center, Chang Gung University, Guishan District, 33302 Taoyuan, Taiwan.
³ Department of Electronic Engineering, Chang Gung University, Guishan District, 33302 Taoyuan, Taiwan.
⁴ School of Electrical Engineering and Computer Science, The Pennsylvania State University, University Park, Pennsylvania 16801, United States.
⁵ School of Information and Communication Engineering, Beijing Information Science & Technology University, Beijing 100101, China.
⁶ Department of Mechanical Engineering, The University of Hong Kong, Pokfulam Road, 999077, Hong Kong.
⁷ Department of Electrical Engineering and Institute of Electronics, National Yang Ming Chiao Tung University, 300 Hsinchu, Taiwan.
⁸ Department of Nephrology, Chang Gung Memorial Hospital, Guishan District, 33305, Linkou, Taiwan.
⁹ Department of Materials Engineering, Ming Chi University of Technology, Taishan District, 24301 New Taipei City, Taiwan.

Abstract

The fast development of the Internet of things (IoT) promises to deliver convenience to human life. However, a huge amount of the data is constantly generated, transmitted, processed, and stored, posing significant security challenges. The currently available security protocols and encryption techniques are mostly based on software algorithms and pseudorandom number generators that are vulnerable to attacks. A true random number generator (TRNG) based on devices using stochastically physical phenomena has been proposed for auditory data encryption and trusted communication. In the current study, a Bi₂O₂Se-based memristive TRNG is demonstrated for security applications. Compared with traditional metal-insulator-metal based memristors, or other two-dimensional material-based memristors, the Bi₂O₂Se layer as electrode with non-van der Waals interface, high carrier mobility, air stability, extreme low thermal conductivity, as well as vertical surface resistive switching shows intrinsic stochasticity and complexity in a memristive true analogue/digital random number generation. Moreover, those analogue/digital random number generation processes are proved to be resilient for machine learning prediction.

Keywords: Bi2O2Se; Diffie−Hellman key exchange; Shapley value; long short-term memory; memristor; random telegraph noise; true random number generator.