A Closer Look at the Chaotic Ring Oscillators based TRNG Design

被引：0
作者：
Su S. [1 ]
Yang B. [1 ]
Rožić V. [1 ,2 ]
Yang M. [1 ]
Zhu M. [3 ]
Wei S. [1 ]
Liu L. [1 ]
机构：
[1] Tsinghua University, Bejing
[2] KU Leuven, Leuven
[3] Wuxi Micro Innovation Integrated Circuit Design Co., Ltd, Wuxi
来源：
IACR Transactions on Cryptographic Hardware and Embedded Systems | 2023年 / 2023卷 / 02期
基金：
中国国家自然科学基金;
关键词：
design methodology; FIRO-/GARO-based TRNGs; gate-level implementation guidelines; online test; periodic oscillation;
D O I：
10.46586/tches.v2023.i2.381-417
中图分类号：
学科分类号：
摘要：
TRNG is an essential component for security applications. A vulnerable TRNG could be exploited to facilitate potential attacks or be related to a reduced key space, and eventually results in a compromised cryptographic system. A digital FIRO-/GARO-based TRNG with high throughput and high entropy rate was introduced by Jovan Dj. Golić (TC’06). However, the fact that periodic oscillation is a main failure of FIRO-/GARO-based TRNGs is noticed in the paper (Markus Dichtl, ePrint’15). We verify this problem and estimate the consequential entropy loss using Lyapunov exponents and the test suite of the NIST SP 800-90B standard. To address the problem of periodic oscillations, we propose several implementation guidelines based on a gate-level model, a design methodology to build a reliable GARO-based TRNG, and an online test to improve the robustness of FIRO-/GARO-based TRNGs. The gate-level implementation guidelines illustrate the causes of periodic oscillations, which are verified by actual implementation and bifurcation diagram. Based on the design methodology, a suitable feedback polynomial can be selected by evaluating the feedback polynomials. The analysis and understanding of periodic oscillation and FIRO-/GARO-based TRNGs are deepened by delay adjustment. A TRNG with the selected feedback polynomial may occasionally enter periodic oscillations, due to active attacks and the delay inconstancy of implementations. This inconstancy might be caused by self-heating, temperature and voltage fluctuation, and the process variation among different silicon chips. Thus, an online test module, as one indispensable component of TRNGs, is proposed to detect periodic oscillations. The detected periodic oscillation can be eliminated by adjusting feedback polynomial or delays to improve the robustness. The online test module is composed of a lightweight and responsive detector with a high detection rate, outperforming the existing detector design and statistical tests. The areas, power consumptions and frequencies are evaluated based on the ASIC implementations of a GARO, the sampling circuit and the online test module. The gate-level implementation guidelines promote the future establishment of the stochastic model of FIRO-/GARO-based TRNGs with a deeper understanding. © 2023, Ruhr-University of Bochum. All rights reserved.
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页码：381 / 417
页数：36
相关论文
共 33 条
  • [1] Cicek Ihsan, Dundar Gunhan, A chaos based integrated jitter booster circuit for true random number generators, 21st European Conference on Circuit Theory and Design, ECCTD 2013, pp. 1-4, (2013)
  • [2] Dichtl Markus, Golic Jovan Dj., High-speed true random number generation with logic gates only, Cryptographic Hardware and Embedded Systems-CHES 2007, 9th International Workshop, Vienna, Austria, September 10-13, 2007, Proceedings, volume 4727 of Lecture Notes in Computer Science, pp. 45-62, (2007)
  • [3] Dichtl Markus, How to predict the output of a hardware random number generator, Cryptographic Hardware and Embedded Systems-CHES 2003, 5th International Workshop, Cologne, Germany, September 8-10, 2003, Proceedings, volume 2779 of Lecture Notes in Computer Science, pp. 181-188, (2003)
  • [4] Dichtl Markus, Fibonacci ring oscillators as true random number generators-A security risk, IACR Cryptol. ePrint Arch, 2015, (2015)
  • [5] Drutarovsky Milos, Simka Martin, Fischer Viktor, Celle Frederic, A simple pll-based true random number generator for embedded digital systems, Comput. Artif. Intel l, 23, 5, pp. 501-515, (2004)
  • [6] Fan Lingyan, Long Yongping, Luo Jianjun, Zhu Liangliang, Liu Hailuan, A true random number generator based on meta-stable state, IEICE Electron. Express, 15, 1, (2018)
  • [7] Golic J.D.J., New methods for digital generation and postprocessing of random data, Computers, IEEE Transactions on, 55, pp. 1217-1229, (2006)
  • [8] Haliuk Serhii, Krulikovskyi Oleh, Vovchuk Dmytro, Corinto Fernando, Memristive structure-based chaotic system for PRNG, Symmetry, 14, 1, (2022)
  • [9] Haliuk Serhii, Krulikovskyi Oleh, Vovchuk Dmytro, Corinto Fernando, Memristive structure-based chaotic system for PRNG, Symmetry, 14, 1, (2022)
  • [10] Hall Timothy, McKay Kerry, User’s guide to running the draft nist sp 800-90b section 9 entropy estimation tests, (2015)
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