基于参数公差变化半导体激光器的混沌RNG

Sara Ahmed, Nancy Alshaer, T. Ismail
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引用次数: 1

摘要

在大多数密码系统中,随机数在保证保密性方面起着至关重要的作用。利用混沌光信号实现高速随机数。它可以通过使用一个或多个具有外部光反馈的半导体激光器来产生。然而,该系统面临两个主要问题:峰值平均功率比(PAPR)过高和参数变化。这些问题严重影响了生成的比特流的随机性。在本文中,我们使用非线性压缩技术对产生的信号在量化之前进行对比,以避免PAPR的影响。此外,我们通过使用来自两个不同生成的比特流的高级加密标准(AES)算法来开发后处理阶段。非线性量化和后处理这两个集成的阶段被配置为实现NIST和DIEHARD统计测试套件保证的高效随机数的生成。最后,在±20%的公差范围内对系统进行了验证,包括外镜反射率、外腔长度和归一化注入电流。结果表明,该系统在参数配置允许的情况下也能生成真正的随机数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Chaos-Based RNG using Semiconductor Lasers with Parameters Variation Tolerance
Random numbers play an essential role in guaranteeing secrecy in most cryptographic systems. A chaotic optical signal is exploited to achieve high-speed random numbers. It could be generated by using one or more semiconductor lasers with external optical feedback. However, this system faces two major issues, high peak to average power ratio (PAPR) and parameter variations. These issues highly affected the randomness of the generated bitstreams. In this paper, we use a non-linear compression technique to compand the generated signal before it is quantized to avoid the effects of the PAPR. Also, we develop the post-processing stage by using advanced encryption standard (AES) algorithm feeds from two different generated bitstreams. These two integrated stages, non-linear quantization, and post-processing are configured to achieve a generation of a efficient random number guaranteed by NIST and DIEHARD statistical test suites. Finally, the proposed system is verified at parameter variation of ±20% tolerance including external mirror reflectivity, external cavity length, and normalized injection current. The results show that the proposed system could generate truly random numbers even with parameters configuration tolerance.
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