Fast True Random Number Generator Based on Chaotic Oscillation in Self-Feedback Weakly Coupled Superlattices

Autor: Yanfei Liu, Cheng Chen, Dong Dong Yang, Qi Li, Xiujian Li
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: IEEE Access, Vol 8, Pp 182693-182703 (2020)
Druh dokumentu: article
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2020.3028735
Popis: Random numbers play a vital role in communications and cryptography. However, most existing true random number generators have difficulty in satisfying the requirements of high-speed communications due to their complexity and bulkiness, or low speed limitations due to equipment bandwidth. Then, the all-electron true random number generator was presented based on GaAs/Al0.45Ga0.55As superlattices conducted under direct current bias at room temperature, which not only possesses the characteristics of miniaturization but also generates random numbers at rates up to the Gbit/s. However, the bit rate of random number generators based on superlattices is still much slower compared to chaotic laser random number generators. In order to generate higher-rate random numbers, we modified a DC-excited superlattice and then redirected the signal generated by the superlattice back into itself, thus introducing a self-feedback, and achieved a self-feedback superlattice true random number generator. This improvement makes the superlattice have a more detailed signal shape, a more effective signal amplitude, and with lower power consumption. Therefore, these advances made the self-feedback superlattice more suitable for generating random numbers. Moreover, we propose a new post-processing method, called the adjacent bits reversal exclusive-or. This method can reduce the sequence bias and correlation without discarding any random bit. The random number obtained by the self-feedback superlattice at a sampling rate of 10 GS/s passed the triple standard deviation test and the random number standard test (NIST SP 800-22), indicating that it possessed good statistical properties as a miniaturized random number generator.
Databáze: Directory of Open Access Journals