| Title | An Empirical Study on the Quality of Entropy Sources in Linux Random Number Generator |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Du, Mingshu, Ma, Yuan, Lv, Na, Chen, Tianyu, Jia, Shijie, Zheng, Fangyu |
| Conference Name | ICC 2022 - IEEE International Conference on Communications |
| Keywords | Cognition, communication security, composability, compositionality, Conferences, Encryption, Entropy, entropy sources, Estimation, Generators, Linux, Linux Operating System Security, Metrics, pubcrawl, random number generators, resilience, Resiliency |
| Abstract | Random numbers are essential for communications security, as they are widely employed as secret keys and other critical parameters of cryptographic algorithms. The Linux random number generator (LRNG) is the most popular open-source software-based random number generator (RNG). The security of LRNG is influenced by the overall design, especially the quality of entropy sources. Therefore, it is necessary to assess and quantify the quality of the entropy sources which contribute the main randomness to RNGs. In this paper, we perform an empirical study on the quality of entropy sources in LRNG with Linux kernel 5.6, and provide the following two findings. We first analyze two important entropy sources: jiffies and cycles, and propose a method to predict jiffies by cycles with high accuracy. The results indicate that, the jiffies can be correctly predicted thus contain almost no entropy in the condition of knowing cycles. The other important finding is the failure of interrupt cycles during system boot. The lower bits of cycles caused by interrupts contain little entropy, which is contrary to our traditional cognition that lower bits have more entropy. We believe these findings are of great significance to improve the efficiency and security of the RNG design on software platforms. |
| Notes | ISSN: 1938-1883 |
| DOI | 10.1109/ICC45855.2022.9839285 |
| Citation Key | du_empirical_2022 |
An Empirical Study on the Quality of Entropy Sources in Linux Random Number Generator