Optical physical unclonable functions (PUFs) are gaining significant attention in hardware security due to their intrinsically unpredictable quasi-chaotic behavior, rendering it particularly suitable for random key generation. However, systematic evaluation and quantitative criteria for speckle quality remain largely unexplored, with microscopic-level analyses still lacking, thereby severely hindering practical application. To address this, we conduct a comprehensive statistical and information-theoretic evaluation by extracting speckle information from diverse perspectives, with particular emphasis on the gray-level co-occurrence matrix and its higher-order statistical features. Accordingly, it is demonstrated that speckle patterns satisfying the sampling theorem reveal strong inherent randomness and are well suited for secret-key generation. Finally, we establish a quantitative speckle quality discrimination framework that integrates multiple information-theoretic means for high-quality cryptographic key generation. The resulting random bit streams successfully pass stringent Dieharder randomness tests and exhibit a verified min-entropy exceeding 0.995 bits per bit. Our results provide a potential research avenue for improving the randomness of optical PUF-based secret-key generation systems, advancing their real-world deployment in information security.
Optical physical unclonable functions (PUFs) are gaining significant attention in hardware security due to their intrinsically unpredictable quasi-chaotic behavior, rendering it particularly suitable for random key generation. However, systematic evaluation and quantitative criteria for speckle quality remain largely unexplored, with microscopic-level analyses still lacking, thereby severely hindering practical application. To address this, we conduct a comprehensive statistical and information-theoretic evaluation by extracting speckle information from diverse perspectives, with particular emphasis on the gray-level co-occurrence matrix and its higher-order statistical features. Accordingly, it is demonstrated that speckle patterns satisfying the sampling theorem reveal strong inherent randomness and are well suited for secret-key generation. Finally, we establish a quantitative speckle quality discrimination framework that integrates multiple information-theoretic means for high-quality cryptographic key generation. The resulting random bit streams successfully pass stringent Dieharder randomness tests and exhibit a verified min-entropy exceeding 0.995 bits per bit. Our results provide a potential research avenue for improving the randomness of optical PUF-based secret-key generation systems, advancing their real-world deployment in information security.
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.
We investigate the use of twin optical fingerprints derived from correlated physical unclonable functions (PUFs), as a hardware-based platform for cryptographic key generation and distribution. Each fingerprint is associated with a random, yet reproducible speckle pattern, generated when coherent light is scattered by a disordered optical structure. We consider a pair of correlated optical PUFs, and study the conditions under which two honest parties can establish a common secret key, despite fabrication-induced variability and environmental noise. An explicit information-theoretic key-agreement protocol is developed, incorporating secure sketches, error reconciliation, and privacy amplification. We quantify information leakage due to public helper data, and derive lower bounds on the length of the final secret key. The analysis identifies the noise regimes in which secure key agreement is feasible, and examines the performance of both practical and near-capacity reconciliation schemes. Finally, we discuss how twin optical PUFs could be integrated into quantum key distribution (QKD) networks, as a mechanism for establishing an initial pre-shared secret key between two honest users, without relying on computational assumptions or trusted third parties.
In this paper, we present an in-depth analysis for entropy source based on optical physical unclonable functions (PUFs). The randomness of speckle patterns is elaborated essentially according to its statistical characteristics. Various factors affecting the source of entropy have been analyzed in detail, including wavefront modulation, sensitivity, and universality of the optical PUF, and bit-depth settings of captured speckle patterns. In view of the above considerations, we demonstrate that the entropy source can achieve an ultra-high min-entropy (>0.985 bits/bit) while maintaining a high extraction rate of 75% and also verify its independent and identically distributed nature. These results provide an in-depth and comprehensive understanding of the developed entropy source and offer a firm foundation for its practical use.
Optical physical unclonable functions (PUFs) have emerged as a promising cryptographic primitive for next-generation security. However, to harmonize with various modern networks, conventional optical PUF is inadequate due to a rigid key space with a fixed specification. This study implements hierarchically controllable randomness sources for multi-level key generation, exploiting speckle characteristics. By adjusting illumination diameter, the speckle size can be modulated, allowing the extraction of three-level keys with various lengths: 64, 256, and 1,024 bits. Performance evaluation reveals that all levels are superb in uniformity, uniqueness, reproducibility, and randomness. Moreover, it is proposed two feasible applications. The first is a hierarchical authentication architecture that spans from Internet of Things (IoT) devices to sensitive information, balancing security and resources. The second is a multi-stage image encryption algorithm, exhibiting holocryptic performance superior to conventional XOR-based encryption. This versatile platform sets a new paradigm for optical PUF, establishing a foundation for robust and expandable next-generation security.
With the rapid expansion of digital communication and the Internet of Things (IoT), hardware-level security and anti-counterfeiting technologies have become increasingly important. Traditional cryptographic systems depend on mathematically generated keys, which are vulnerable to duplication and physical attacks. In contrast, Physical Unclonable Functions (PUFs) utilize inherent physical randomness to produce unique, unpredictable responses, offering a hardware root of trust for secure authentication. Among various PUF implementations, optical PUFs (O-PUFs) have attracted attention due to their high entropy density, non-contact readout, and immunity to electromagnetic interference. These systems exploit light–matter interactions, such as scattering, reflection, and emission to generate random optical fingerprints. In recent years, photoluminescent (PL) materials have emerged as promising candidates for constructing material-based optical PUFs. Their intrinsic emission randomness, strong optical signals, and tunable luminescence enable secure encoding without complex nanofabrication. Materials such as perovskite quantum dots and lanthanide-based metal–organic frameworks (MOFs) combine high photoluminescence efficiency, environmental stability, and low-cost processability, making them ideal for scalable optical authentication applications. This thesis explores the development and performance evaluation of photoluminescent based PUFs for optical security and anti-counterfeiting. Three types of luminescent materials, namely perovskite quantum dots, lanthanide-based MOFs, and intermolecular charge-transfer (CT) complexes are qualitatively analyzed as potential optical PUF platforms. A particular focus is placed on the statistical evaluation of Terbium-based MOFs (Tb-MOFs) and CT complexes. For Tb-MOFs, two entropy sources are examined: the spatial distribution of MOF microstructures and the randomness in PL intensity. Similarly, CT complexes are evaluated based on their disordered geometric topology. Standardized image processing, including optical imaging, grayscale conversion, and binarization, is employed to extract PUF features. Quantitative metrics such as uniqueness, reliability, and encoding capacity are analyzed. The results demonstrate that both Tb-MOF and CT-based systems achieve high encoding capacity and stable reproducibility within a sub-millimeter scale. This study validates the feasibility of luminescent materials as robust optical PUFs and provides a foundation for scalable, photostable, and intelligent optical authentication systems
Laser speckle has been proposed in a number of papers as a high entropy source of unpredictable bits for use in security applications. Bit strings derived from speckle can be used for a variety of security purposes such as in identification, authentication, anti-counterfeiting, secure key storage, random number generation and tamper protection. The choice of laser speckle as a source of random keys is quite natural, given the chaotic properties of speckle. However, this same chaotic behaviour also causes reproducibility problems. Cryptographic protocols require either zero noise or very low noise in their inputs; hence the issue of error rates is critical to applications of laser speckle in cryptography. Most of the literature uses an error reduction method based on Gabor filtering. Though the method is successful, it has not been thoroughly analysed.\nIn this paper we present a statistical analysis of Gabor-filtered speckle patterns. We introduce a model in which perturbations are described as random phase changes in the source plane. Using this model we compute the second- and fourth-order statistics of Gabor coefficients. We determine the mutual information of perturbed and unperturbed Gabor coefficients and the bit error rate in the derived bit string. The mutual information provides an absolute upper bound on the number of secure bits that can be reproducibly extracted from noisy measurements.