Analysis of random noise generated by graphic processing units

Yongjin Yeom, Taeill Yoo
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引用次数: 0

Abstract

Random number generators are essential in modern cryptography. The security of a cryptographic scheme can be achieved under the assumption that the system uses ideal random numbers to produce sensitive security parameters such as encryption keys and initial vectors. The weakness of the random number generator makes the entire cryptographic system insecure. In particular, the lack of entropy sources leads to predictable output random bits so that secret information can be guessed by malicious attackers. Therefore, it is important to collect sufficient entropy from physical noise sources. In this paper, we consider graphics processing units (GPUs) as an entropy source. From the race conditions in the parallel computations on a GPU, we can harvest sufficient entropy for cryptography. Using the entropy estimations in NIST SP 800-90B, the amount of entropy is estimated and compared with other physical sources.
分析由图形处理单元产生的随机噪声
随机数生成器在现代密码学中是必不可少的。在假设系统使用理想随机数产生加密密钥和初始向量等敏感安全参数的情况下,可以实现加密方案的安全性。随机数生成器的弱点使得整个密码系统不安全。特别是,缺乏熵源会导致可预测的输出随机比特,从而使秘密信息可以被恶意攻击者猜出。因此,从物理噪声源中收集足够的熵是很重要的。在本文中,我们将图形处理单元(gpu)视为熵源。从GPU上并行计算的竞争条件中,我们可以获得足够的加密熵。利用NIST SP 800-90B中的熵估计,估计了熵的数量,并与其他物理源进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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