| Literature DB >> 35333049 |
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 Lai2,3,8,9.
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.Entities:
Keywords: Bi2O2Se; Diffie−Hellman key exchange; Shapley value; long short-term memory; memristor; random telegraph noise; true random number generator
Year: 2022 PMID: 35333049 PMCID: PMC9048684 DOI: 10.1021/acsnano.2c01784
Source DB: PubMed Journal: ACS Nano ISSN: 1936-0851 Impact factor: 18.027