We demonstrate a random bit streaming system that uses a chaotic laser as its physical entropy source. By performing real-time bit manipulation for bias reduction, we were able to provide the memory of a personal computer with a constant supply of ready-to-use physical random bits at a throughput of up to 4 Gbps. We pay special attention to the end-to-end entropy source model describing how the entropy from physical sources is converted into bit entropy. We confirmed the statistical quality of the generated random bits by revealing the pass rate of the NIST SP800-22 test suite to be 65 % to 75 %, which is commonly considered acceptable for a reliable random bit generator. We also confirmed the stable operation of our random bit steaming system with long-term bias monitoring.
We demonstrate a random bit streaming system that uses a chaotic laser as its physical entropy source. By performing real-time bit manipulation for bias reduction, we were able to provide the memory of a personal computer with a constant supply of ready-to-use physical random bits at a throughput of up to 4 Gbps. We pay special attention to the end-to-end entropy source model describing how the entropy from physical sources is converted into bit entropy. We confirmed the statistical quality of the generated random bits by revealing the pass rate of the NIST SP800-22 test suite to be 65 % to 75 %, which is commonly considered acceptable for a reliable random bit generator. We also confirmed the stable operation of our random bit steaming system with long-term bias monitoring.
Using two mutually coupled semiconductor lasers (MC-SLs) outputs as chaotic entropy sources, a scheme for generating Tbits/s ultra-fast physical random bit (PRB) is demonstrated and analyzed experimentally. Firstly, two entropy sources originating from two chaotic outputs of MC-SLs are obtained in parallel. Secondly, by adopting multiple optimized post-processing methods, two PRB streams with the generation rate of 0.56 Tbits/s are extracted from the two entropy sources and their randomness are verified by using NIST Special Publication 800-22 statistical tests. Through merging the two sets of 0.56 Tbits/s PRB streams by an interleaving operation, a third set of 1.12 Tbits/s PRB stream, which meets all the quality criteria of NIST statistical tests, can be further acquired. Finally, after additionally taking into account the restriction of the min-entropy, the generation rate of two sets of PRB stream from the two entropy sources can still attain 0.48 Tbits/s, and then a third set of merging PRB stream is 0.96 Tbits/s. Moreover, for the sequence length of the order of 10 Gbits, the statistical bias and serial correlation coefficient of three sets of PRB streams are also analyzed.
Chaotic light generated by optical feedback semiconductor laser is employed as entropy source. We experimentally obtain random bit sequences of different rates by using a series of processing on chaotic signals, such as photoelectric conversion, analog-digital conversion, and exclusive OR operation. Based on the principle, we develop a 2.5 Gbit/s physical random bit generator prototype which can steadily run for a long time. It can generate random bit sequence at 155 Mbit/s, 622 Mbit/s, 1.25 Gbit/s, 2.5 Gbit/s and so on, whose rates are consistent with the current communication rates. All random bit sequences with different bit rates pass all of the NIST statistical tests. The generated random bits will be used as high-speed real-time physical keys for the one-time padding secure communication.
Generating random bit streams is required in various applications, most notably in cyber-security, which is essential for Internet of Everything applications to enable secure communication between interconnected devices. Ensuring high-quality and robust randomness is crucial to mitigate risks associated with predictability and system compromise. True random numbers provide the highest levels of unpredictability. However, known systematic biases that can emerge from physical imperfections, environmental variations, and device aging in the processes exploited for random number generation must be carefully monitored. This article reports the implementation and characterization of an online procedure for the detection of anomalies in a true random bit stream. It is based on the NIST adaptive proportion and repetition count tests, complemented by statistical analysis relying on the Monobit and RUNS tests. The procedure is implemented in firmware through dedicated hardware accelerators processing configurable-length sequences, with automated anomaly detection triggering alerts after three consecutive threshold violations. The implementation is performed simultaneously with bit stream generation and also provides an estimate of the entropy of the source. A statistical analysis of the results from the NIST procedure to evaluate the symbols of the bit-stream as independently and identically distributed is also performed, leading to a computation of the minimum entropy of the source that cross-checks the previously mentioned estimate. The experimental validation of the approach is performed up the bit streams generated by a quantum, silicon-based entropy source.
Taking the broadband chaotic output from a weak-resonant-cavity Fabry-Perot laser diode (WRC-FPLD) under filtered feedback as a chaotic entropy source, we propose and experimentally demonstrate a scheme for generating fast physical random bits (PRBs) at a rate up to 240 Gbits/s. First, we investigate the dependence of the dynamical properties of the filtered feedback WRC-FPLD on the system parameters, and determine the optimized parameter region for generating wavelength-tunable and broadband chaotic signals. Second, a broadband chaotic signal with a bandwidth beyond 20 GHz output from the WRC-FPLD is sampled and transferred to a digital bit sequence by an 8-bit analog-to-digital converter at a rate of 40 GS/s. Finally, by utilizing multi-bit post-processing method, PRBs is generated at a rate up to 240 Gbits/s, which can pass all the 15 NIST statistics tests and meet the strict criteria of the statistical bias and the serial correlation coefficient.
Generating random bit streams is required in various applications, most notably cyber-security. Ensuring high-quality and robust randomness is crucial to mitigate risks asso-ciated with predictability and system compromise. True random numbers provide the highest unpredictability levels. However, potential biases in the processes exploited for the random number generation must be carefully monitored. This paper reports the implementation and characterization of an on-line procedure for the detection of anomalies in a true random bit stream. It is based on the NIST Adaptive Proportion and Repetition Count tests, complemented by statistical analysis relying on the Monobit and RUNS. The procedure is firmware implemented and performed simultaneously with the bit stream generation, and providing as well an estimate of the entropy of the source. The experimental validation of the approach is performed upon the bit streams generated by a quantum, silicon-based entropy source.
The output modes of random lasers exhibit randomness, making them a potential high-quality physical entropy source for generating random numbers. In this paper, we controlled a low-cost and easily fabricated abalone shell random laser, generating forward and backward coherent random lasers simultaneously in a single channel, resulting in highly diverse mode variations. After post-processing steps such as third-order difference calculations and exclusive-or (XOR) logic operations, we generated a random number sequence for the first time, to the best of our knowledge, based on the temporal fluctuations of biomimetic random laser coherent modes. The instantaneous generation rate reached a preliminary 40 Gbps. Moreover, the random bits satisfy requirements such as random distribution, independence, and absence of bias, successfully passing the NIST SP800-22 standard test, confirming the high quality of the random number sequence.