Details

Autor(en) / Beteiligte

• Zhao, Jiayi
• Chen, Bing
• Wang, Wannian
• Xia, Wentai
• Ye, Jiabao
• Bi, Haoxiong
• Cao, Jifang
• Jin, Chengji
• Yu, Xiao
• Cheng, Ran
• Liu, Yan
• Han, Genquan

Titel

A True Random Number Generator Based on Semiconductor-Vacancies Junction Entropy Source and Square Transform Method

Ist Teil von

• IEEE transactions on electron devices, 2023-10, Vol.70 (10), p.1-5

Ort / Verlag

New York: IEEE

Erscheinungsjahr

2023

Quelle

IEEE Electronic Library Online

Beschreibungen/Notizen

• In this work, we demonstrate a high-throughput true random number generator (TRNG), which passes the National Institute of Standards and Technology (NIST) 800-22 and 800-90B randomness tests. A novel TiN/HfO<inline-formula> <tex-math notation="LaTeX">_{\text{2}}</tex-math> </inline-formula>/n-Si structured semiconductor-vacancies (S-VOs) junction entropy source is developed with an area of 4 F<inline-formula> <tex-math notation="LaTeX">^{\text{2}}</tex-math> </inline-formula>. The TRNGs are implemented by the proposed square transform method in the voltage domain using an analog-to-digital converter (ADC). According to the measured statistical characteristics, the TRNGs exhibit excellent robustness and a high throughput of 1.6 Mbps by experiment and 20 Gbps by theory.