利用物理热噪声在结构上超稳定的1T'二化物中,用于真随机数生成
Yang Liu1,2, Pengyu Liu1, Yingyi Wen1
1Department of Electronic Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR 999077, China.
Nano letters
|November 1, 2024
概括
研究人员使用转移稳定的二化 (MoTe2) 中的导电噪声生成了真正的随机数. 这种方法提供了高通量安全的随机数字,对密码学和AI数据安全应用至关重要.
科学领域:
- 材料科学 材料科学 材料科学
- 凝聚物质物理学 凝聚物质物理学
- 信息安全 信息安全
背景情况:
- 真正的随机数对于安全的研究和工程应用至关重要.
- 生产依赖于强大的物理源.
- 现有的方法可能在速度或安全性方面存在局限性.
研究的目的:
- 为了证明1T'二甲 (MoTe2) 中的导电噪声的真实随机数生成 (TRNG).
- 为了验证噪声作为一个强大的物理源在各种温度下.
- 展示高通量安全随机数生成的实际应用.
主要方法:
- 在结构上超稳定的1T' MoTe2.2中探测导电噪声.
- 分析噪声特征以确认波桑过程和源.
- 使用产生的噪音实现TRNG.
- 在神经网络的生物识别数据掩盖中展示应用.
主要成果:
- 从MoTe2导电噪声中成功生成了真正的随机数.
- 噪声表现出Poisson过程的特征,并且在低温/冷温度下具有强度.
- 实现了高通量安全随机数生成,超过1 Mbit/s.
- 在神经网络中证明有效的生物识别数据保护.
结论:
- 1T'MoTe2是一种可行的材料,可以产生强大的物理噪声.
- 开发的TRNG方法提供高速安全的随机数生成.
- 这项技术在加密,大数据和人工智能安全方面具有重大潜力.
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