Our study introduces a novel approach to true random number generation (TRNG) using speckle patterns generated by laser-engraved holograms on carbon fiber-reinforced polymer (CFRP) composite substrates. Unlike previous methods, our approach simplifies the process by generating the necessary image dataset from a single microscope image of the engraved hologram. We achieve a high extraction ratio of 76 %, demonstrating the effectiveness of our TRNG. Moreover, our method successfully passes rigorous statistical tests proposed by the National Institute of Standards and Technology (NIST), indicating its suitability for cryptographic and secure system applications. This work offers promising implications for enhancing security in various domains, from secure communication networks to IoT devices.
Our study introduces a novel approach to true random number generation (TRNG) using speckle patterns generated by laser-engraved holograms on carbon fiber-reinforced polymer (CFRP) composite substrates. Unlike previous methods, our approach simplifies the process by generating the necessary image dataset from a single microscope image of the engraved hologram. We achieve a high extraction ratio of 76 %, demonstrating the effectiveness of our TRNG. Moreover, our method successfully passes rigorous statistical tests proposed by the National Institute of Standards and Technology (NIST), indicating its suitability for cryptographic and secure system applications. This work offers promising implications for enhancing security in various domains, from secure communication networks to IoT devices.
The development of random number generators (RNGs) using speckle patterns is pivotal for secure encryption key generation, drawing from the recent statistical properties identified in speckle-based imaging. Speckle-based RNG systems generate a sequence of random numbers through the unpredictable and reproducible nature of speckle patterns, ensuring a source of randomness that is independent of algorithms. However, to guarantee their effectiveness and reliability, these systems demand a meticulous and rigorous approach. In this study, we present a blood-inspired RNG system with a microfluidics device, designed to generate random numbers at a rate of 5.5 MHz and a high-speed of 1250 fps. This process is achieved by directing a laser beam through a volumetric scattering medium to procure speckle patterns. Additionally, designed microfluidic device requires only a minimal blood sample of 5 µl to capture these speckle patterns effectively. After implementing the two-pass tuple-output von Neumann debiasing algorithm to counteract statistical biases, we utilized the randomness statistical test suite from the National Institute of Standards and Technology for validation. The generated numbers successfully passed these tests, ensuring their randomness and unpredictability. Our blood-inspired RNG, utilizing whole blood, offers a pathway for affordable, high-output applications in fields like encryption, computer security, and data protection.
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.
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.
Random Number Generators (RNGs) are crucial for applications ranging from cryptography to simulations. Depending on the source of randomness, RNGs are classified into Pseudo-Random Number Generators (PRNGs), True Random Number Generators (TRNGs), and Quantum Random Number Generators (QRNGs). This work presents the end-to-end development of a high-speed, high-efficiency, phase-noise-based QRNG system that taps into the quantum phase noise of a single-frequency laser, with randomness originating from spontaneous emission. Using a self-heterodyne measurement with a semiconductor laser (linewidth ≈ 5.23 GHz) operated near threshold and a $\sim$48 cm fiber delay line, a raw data generation rate of 2.0 Gbps is achieved. To ensure uniform randomness in the QRNG output, robust extraction techniques developed in-house, such as the Toeplitz Strong Extractor (TSE), are used. Randomness validation using the NIST and Diehard test suites confirms that all statistical tests pass at standard confidence levels. The developed system achieves a post-processed generation rate of 1.0 Gbps in operation and attains a Technology Readiness Level (TRL) of 7, approaching TRL 8, making it suitable for real-time secure applications such as cryptographic key generation and stochastic modeling.
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.
In this paper, we design a photonic-based true random number generator (True RNG) which is targeted for cryptographic application .Since all security protocols rely on unpredictability, RNGs for crypto applications must meet stringent requirements. The design employs a single-photon detection to generate a random signal which is useful in producing random output. In contrast with traditionally used of frequency sampler circuitry during bit extraction method, it uses a novel method of randomness extraction based on time interval between two successive random signals. The design comprises an optical setup and extremely compact and digitally random bit extraction circuitry which can be implemented on any advance crypto hardware devices. A NIST statistical test is used to test the randomness of the RNG output and has produced a good result. With the help of this True RNG, the cryptographic implementations can be secure enough from being abused of malicious act.