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ACS Photonics

Optical True Random Number Generator Based on Reconfigurable Ge2Sb2Te5 PUFs

Yiting Yang, Ruijie Hui, Xueguang Lu, Lu Tang, Zaixin Gan, Mo Li, Jian Zhang, Kefan Chen, Feiliang Chen, Wanxia Huang

Published Oct 29, 2024• 8 citations
Publisher

Abstract

True random number generators (TRNGs) are the fundamental building blocks for encryption. Physical unclonable functions (PUFs) prepared based on stochastic processes, with the advantages of being impossible to imitate and tamper with, are a new source for generating high-quality random numbers. However, most proposed PUFs form a fixed structure after preparation; the as-generated random number sequence is thus fixed. In this article, a reconfigurable optical PUF/TRNG is fabricated by utilizing the phase change properties of the disordered Ge 2 Sb 2 Te 5 (GST) nanocrystalline film. By heating and holding the GST film, its crystallization ratio can be manipulated, generating multiple sets of uncorrelated speckle patterns, which can be converted into multiple random arrays by binary digitization. The random array was verified to have good randomness by the National Institute of Standards and Technology (NIST) randomness test and the DIEHARD(ER) test suites. The proposed true random number generator can be used as a secret key to complete authentication or encryption with high security and high stability.

DOI
10.1021/acsphotonics.4c01148

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True random number generators (TRNGs) are the fundamental building blocks for encryption. Physical unclonable functions (PUFs) prepared based on stochastic processes, with the advantages of being impossible to imitate and tamper with, are a new source for generating high-quality random numbers. However, most proposed PUFs form a fixed structure after preparation; the as-generated random number sequence is thus fixed. In this article, a reconfigurable optical PUF/TRNG is fabricated by utilizing the phase change properties of the disordered Ge 2 Sb 2 Te 5 (GST) nanocrystalline film. By heating and holding the GST film, its crystallization ratio can be manipulated, generating multiple sets of uncorrelated speckle patterns, which can be converted into multiple random arrays by binary digitization. The random array was verified to have good randomness by the National Institute of Standards and Technology (NIST) randomness test and the DIEHARD(ER) test suites. The proposed true random number generator can be used as a secret key to complete authentication or encryption with high security and high stability.
Random number generators (RNG) are fundamental to cryptographic systems, requiring high entropy, unpredictability, and resistance to cloning attacks. This work proposes RNG based on optical physical unclonable function (PUF) that uses random scattering of structured vortex beams through rough surface. The inherent disorder of the scattering medium with tunable beam parameters like vortex order, provides a rich source of physical randomness. The generated speckle patterns are processed using a post processing algorithm to produce random sequences at a rate of 1.42 Gbps. The statistical quality of the sequences is evaluated using the NIST SP 800-22, AIS-31, and Dieharder test suites, which meet the required randomness criteria. Further assessment using entropies and Kolmogorov complexity shows high entropy and algorithmic randomness. The physical unclonability and uniqueness are verified through inter-device hamming distances, Pearson correlation of sequences obtained from different spatial regions and vortex orders, revealing negligible correlations. To assess resilience against data based adversaries, machine learning modeling attacks are performed. The prediction accuracies remain close to random guessing, showing resistance to learning based cloning and response prediction attacks. These results establish the proposed optical PUF method as a high speed, physically unclonable, and machine learning resistant source of random numbers for secure cryptographic applications.
This paper presents a high-throughput true random number generator (TRNG) based on optical speckle patterns generated by illuminating natural plant leaves as biological physical unclonable functions (PUFs). A coherent He–Ne laser produces stochastic far-field speckle fields that are captured by a CMOS camera and converted into random bitstreams using a clearly defined post-processing pipeline. The full extraction procedure— including binary quantization, Von Neumann debiasing, and statistical balancing—is formalized in Algorithm 1 to support reproducibility. Experimental validation is performed using a 38-s dataset (1100 frames), and long-term stability is demonstrated through a 2-hour continuous recording. All evaluated segments show near-ideal entropy (0.9999991 bits/bit), balanced bit distributions, and zero-mean autocorrelation, confirming the robustness of the biological scattering medium over extended durations. After debiasing, the system achieves an effective throughput of approximately 75 Mbit/s, aligning with requirements for cryptographic and security-critical applications. The optical setup is compact and compatible with laser-diode sources and embedded imaging modules, enabling future development of portable, low-power speckle-based TRNG systems.
In this paper we reconsider Physical Unclonable Functions based on the traditional approach of optical scattering to randomly disordered optical media. These devices have the major advantage of utilization of simple and very low-cost technology and therefore the potential to be installed all over the network providing critical cybersecurity operations such authentication, real time cryptographic key generation and generation of trues random sequences. To comply with the requirements of the aforementioned operations, critical issues must be resolved. We propose and implement algorithms for the generation of an almost unlimited number of uncorrelated optical challenges. We show experimentally that the uncorrelated challenges result in optical speckle which, after the proper numerical processing, produce true random sequences. Moreover, we determine the optimal illumination conditions to achieve the best possible performance in terms of robustness and unpredictability. Last but not least, we studied the resilience of the PUF against machine learning attacks. We conclude experimentally that under certain illuminating conditions and using the aforementioned uncorrelated challenges, the network cannot predict the responses even after being trained with a very large number of challenge responses (24,000 pairs).
In high-throughput network security applications, physical unclonable functions (PUFs) employing fixed mapping mechanisms are vulnerable to machine learning attacks. Reconfigurable PUFs can improve security by altering their mapping states, but often face constraints of limited reconfigurability, irreversible controllability, or high hardware overhead. Here, reversible and reconfigurable optical PUFs, 2RO-PUFs, were developed by two-beam manipulation of photothermal-sensitive scatterers with a precisely controllable phase transition. Experimental results verify that the programmed scatters and resultant speckle patterns exhibit deterministic and repeatable reconfigurability while maintaining cryptographic robustness. As demonstrated in a novel Internet of Things framework, the introduction of optically controlled speckle formation into PUFs frameworks enhances cryptographic security and flexibility while alleviating storage and computational overhead.
This paper presents a lightweight true random number generator (TRNG) using beta radiation that is useful for Internet of Things (IoT) security. In general, a random number generator (RNG) is required for all secure communication devices because random numbers are needed to generate encryption keys. Most RNGs are computer algorithms and use physical noise as their seed. However, it is difficult to obtain physical noise in small IoT devices. Since IoT security functions are required in almost all countries, IoT devices must be equipped with security algorithms that can pass the cryptographic module validation programs of each country. In this regard, it is very cumbersome to embed security algorithms, random number generation algorithms, and even physical noise sources in small IoT devices. Therefore, this paper introduces a lightweight TRNG comprising a thin-film beta-radiation source and integrated circuits (ICs). Although the ICs are currently being designed, the IC design was functionally verified at the board level. Our random numbers are output from a verification board and tested according to National Institute of Standards and Technology standards.
True randomness is a basic necessity of secure cryptography. This secures the reliability of encryption keys, digital signatures and authentication mechanisms. Classical random number generators based on deterministic algorithms can introduce patterns and decrease reliability. This paper introduces a Quantum True Random Number Generator (QTRNG) takes advantage of the intrinsic unpredictability of quantum mechanics. The proposed quantum circuit usesRY(π/2)R Y(\pi / 2)RY(π/2)andRZ(π/2)R Z(\pi / 2)RZ(π/2)rotations to create superposition states like Hadamard operation. These gates control the phase and orientation of qubits on the Bloch sphere yields measurement outcomes are inherently random. The resulting distributions are unbiased and balanced offers a source of true randomness. The quality of the generated bitstrings is verified using statistical tests such as the NIST SP 800-22, SP 800-90 test suites and autocorrelation tests. The measurements show high entropy, uniform distribution and low bias satisfy the basic requirements for cryptographic security. Phase-based quantum operations provide an efficient for producing high-quality quantum randomness facilitates the construction of effective quantum-secure cryptographic systems.