The rapid proliferation of IoT devices has heightened the demand for efficient security solutions. Optical physical unclonable functions (O-PUFs) present a promising alternative due to their intrinsic strong physical randomness and unclonability. However, conventional O-PUFs are restricted by fixed configurations, leading to limited key generation capacity. This work proposes a multi-level modulated O-PUF key generation scheme. For phase-encoded challenges, the proposed scheme introduces a diffuser to distort the wavefront and enhance modulation sensitivity. Dynamic modulation is realized by the rotation and translation of the O-PUF and the adjustment of a half-wave plate and a linear polarizer. A key generation system with ZnO-particle-embedded O-PUF is demonstrated, and a simulated annealing algorithm is introduced to optimize phase encoding for enhanced response randomness. A logistic regression-based matched filter is designed to improve the entropy of initial keys, and a fuzzy extractor enables the generation of a reliable, unique, large-capacity cryptographic key. This work advances optical PUF key generation and provides a robust foundation for cryptographic security.
The rapid proliferation of IoT devices has heightened the demand for efficient security solutions. Optical physical unclonable functions (O-PUFs) present a promising alternative due to their intrinsic strong physical randomness and unclonability. However, conventional O-PUFs are restricted by fixed configurations, leading to limited key generation capacity. This work proposes a multi-level modulated O-PUF key generation scheme. For phase-encoded challenges, the proposed scheme introduces a diffuser to distort the wavefront and enhance modulation sensitivity. Dynamic modulation is realized by the rotation and translation of the O-PUF and the adjustment of a half-wave plate and a linear polarizer. A key generation system with ZnO-particle-embedded O-PUF is demonstrated, and a simulated annealing algorithm is introduced to optimize phase encoding for enhanced response randomness. A logistic regression-based matched filter is designed to improve the entropy of initial keys, and a fuzzy extractor enables the generation of a reliable, unique, large-capacity cryptographic key. This work advances optical PUF key generation and provides a robust foundation for cryptographic security.
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.
Abstract A physical unclonable function (PUF) device leverages manufacturing randomness to generate a unique fingerprint for secure authentication, encryption, and counterfeit prevention. Optical PUFs (OPUFs) have gained prominence due to their strong security, light‐based challenge‐response mechanisms, and potential for quantum‐secure encryption. These devices have promising applications for hardware security, authentication, cryptographic key generation, and anti‐counterfeiting measures across multiple industries. This review enlightens the diverse material platforms used for OPUFs, ranging from fiber optics and liquid crystals to advanced semiconductor nanocrystals and plasmonic metasurfaces, each offering distinct optical characteristics that impact security strength. While no single material system dominates the field, hybrid and multi‐model approaches integrating low‐dimensional materials are being explored to enhance reliability and scalability. Finally, the challenges and future perspectives are outlined, including adaptive OPUFs architectures, utilizing artificial intelligence (AI) for challenge‐response generation, and their integration into quantum communication networks, highlighting how next‐generation semiconductor materials can further advance OPUFs technologies.
A physically unclonable function (PUF) is a promising hardware-based cryptographic primitive to prevent confidential information leakage. However, conventional techniques, such as weak and strong PUFs, have limitations in overcoming the trade-off between security and storage volume. This study introduces nanoseed-based PUFs that overcome the drawbacks of conventional PUFs using optical and electrical randomness originated from nanoseeds and a unique on-demand cryptographic algorithm. Ideally mixed PbS quantum dots and Ag nanocrystals in the same medium are exploited as nanoseeds to simultaneously promote independent optical and electrical randomness. The number of secured keys that can be generated on-demand by combining the optical and electrical features in parallel using shuffling method is almost infinite (>10 58741 per square millimeter). The proposed PUF achieves a near-ideal Hamming distance in uniqueness and randomness tests, validating its cryptographic efficacy. Last, storage-free and on-demand PUF with the shuffling method are demonstrated using smartphones, realizing manufacturer-/user-friendly cryptography system.
The rapid expansion of the Internet of Things (IoT) has significantly raised concerns over secure identification and authentication of IoT devices. While physical unclonable function (PUF)-based anticounterfeiting cryptography shows promise, implementing multi-factor authentication (MFA) system with resource-constrained PUF device remains a significant challenge. Here, we demonstrate a multidimensional-encoded optical PUF fabricated with multi-color quantum dots (mQDs), resilient to machine learning attacks, for use in anticounterfeiting MFA. Randomly distributed mQDs in a periodic nanostructure fabricated via nanoimprint lithography generate spatially chaotic, unpredictable multiple security keys when ultraviolet (UV) light is only illuminated. Photoluminescence measurements revealed irregular mQD emission, where disordered distribution-induced Förster resonant energy transfer produces unpredictable color patterns. Our PUF-induced multiple keys were validated through advanced PUF metrics like uniformity, uniqueness, correlation factor, entropy, and even resilience to machine learning attack. We further demonstrate efficient implementation of a cryptography protocol with MFA system for IoT applications using mQDs-based optical PUFs. Material systems with physical unclonable functions (PUF) are needed for secure authentication. Here, a multidimensional-encoded optical PUF fabricated with multi-color quantum dots is demonstrated, for multi-factor authentication.
The increased prevalence of the Internet of Things (IoT) and the integration of digital technology into our daily lives have given rise to heightened security risks and the need for more robust security measures. In response to these challenges, physical unclonable functions (PUFs) have emerged as promising solution, offering a highly secure method to generate unpredictable and unique random digital values by leveraging inherent physical characteristics. However, traditional PUFs implementations often require complex hardware and circuitry, which can add to the cost and complexity of the system. We present a novel approach using a random wrinkles PUF (rw-PUF) based on an optically anisotropic, facile, simple, and cost-effective material. These wrinkles contain randomly oriented liquid crystal molecules, resulting in a two-dimensional retardation map corresponding to a complex birefringence pattern. Additionally, our proposed technique allows for customization based on specific requirements using a spatial light modulator, enabling fast fabrication. The random wrinkles PUF has the capability to store multiple data sets within a single PUF without the need for physical alterations. Furthermore, we introduce a concept called 'polyhedron authentication,' which utilizes three-dimensional information storage in a voxelated random wrinkles PUF. This approach demonstrates the feasibility of implementing high-level security technology by leveraging the unique properties of the rw-PUF.
In this paper, we propose a new asymmetric cryptosystem for phase image encryption, using the physically unclonable functions (PUFs) as security keys. For encryption, the original amplitude image is first converted into a phase image and modulated with a PUF to obtain a complex image. This complex image is then illuminated with a plane wave, and the complex wavefront at a distance d is recorded. The real part of the complex wavefront is further processed to obtain the encrypted image and the imaginary part is kept as the private key. The polar decomposition approach is utilized to generate two more private security keys and to enable the multi-user capability in the cryptosystem. Numerical simulations confirm the feasibility of the proposed method.