Data proliferation in the digital age necessitates robust encryption techniques to protect information privacy. Optical encryption leverages the multiple degrees of freedom inherent in light waves to encode information with parallel processing and enhanced security features. However, implementations of large-scale, high-security optical encryption have largely remained theoretical or limited to digital simulations due to hardware constraints, signal-to-noise ratio challenges, and precision fabrication of encoding elements. Here, we present an optical encryption platform utilizing scattering multiplexing ptychography, simultaneously enhancing security and throughput. Unlike optical encoders which rely on computer-generated randomness, our approach leverages the inherent complexity of light scattering as a natural unclonable function. This enables multi-dimensional encoding with superior randomness. Furthermore, the ptychographic configuration expands encryption throughput beyond hardware limitations through spatial multiplexing of different scatterer regions. We propose a hybrid decryption algorithm integrating model- and data-driven strategies, ensuring robust decryption against various sources of measurement noise and communication interference. We achieved optical encryption at a scale of ten-megapixel pixels with 1.23 µm resolution. Communication experiments validate the resilience of our decryption algorithm, yielding high-fidelity results even under extreme transmission conditions characterized by a 20% bit error rate. Our encryption platform offers a holistic solution for large-scale, high-security, and cost-effective cryptography.
Data proliferation in the digital age necessitates robust encryption techniques to protect information privacy. Optical encryption leverages the multiple degrees of freedom inherent in light waves to encode information with parallel processing and enhanced security features. However, implementations of large-scale, high-security optical encryption have largely remained theoretical or limited to digital simulations due to hardware constraints, signal-to-noise ratio challenges, and precision fabrication of encoding elements. Here, we present an optical encryption platform utilizing scattering multiplexing ptychography, simultaneously enhancing security and throughput. Unlike optical encoders which rely on computer-generated randomness, our approach leverages the inherent complexity of light scattering as a natural unclonable function. This enables multi-dimensional encoding with superior randomness. Furthermore, the ptychographic configuration expands encryption throughput beyond hardware limitations through spatial multiplexing of different scatterer regions. We propose a hybrid decryption algorithm integrating model- and data-driven strategies, ensuring robust decryption against various sources of measurement noise and communication interference. We achieved optical encryption at a scale of ten-megapixel pixels with 1.23 µm resolution. Communication experiments validate the resilience of our decryption algorithm, yielding high-fidelity results even under extreme transmission conditions characterized by a 20% bit error rate. Our encryption platform offers a holistic solution for large-scale, high-security, and cost-effective cryptography.
Abstract Optical encryption is an emerging technique that uses optical systems to securely encode and decode information for data transmission. In this study, we present an integrated optical encryption platform that consists of a scattering-augmented ptychographic encryption system, a transmission-efficient compressive sampling strategy, and a high-capacity decryption algorithm based on a hybrid model-data driven approach. Our encryption system leverages random light scattering as a physical unclonable function, enabling the encoding of complex object wavefronts with high optical throughput. In contrast to traditional encoders that offer insecure pseudo-randomness, the light scattering process ensures true randomness in the reported platform. To optimize transmission efficiency, we implement a compressive sampling strategy that reduces data transmission volume by at least one order of magnitude. Moreover, we devise a decryption algorithm that merges model-driven optimization with data-driven deep learning, effectively addressing the highly underdetermined retrieval task and providing robust decryption against various measurement noise and communication interference. The efficacy of our system is corroborated by an integrated optical prototype capable of encrypting ten million of pixels within minutes. Communication experiments confirm the resilience of our decryption algorithm, which retrieves high-fidelity results even under extreme transmission conditions characterized by a 20% bit error rate. Our innovative encryption technique presents a comprehensive solution for high-capacity data transmission, fortified by scattering-augmented security.
Multi-object optical encryption has emerged as a promising field for enhancing encryption performance and reducing communication overhead, which can ensure the security of single-pixel imaging. However, it faces some critical challenges like low efficiency, reliance on complex system design, high hardware costs, and the difficulty of parallel encryption with independent decryption, hindering practical deployment. In this work, an illumination pattern construction algorithm is proposed to generate projected basis patterns for parallel optical encryption, while a decoupling algorithm is developed to demodulate coupled measurements to recover Hadamard spectrum for each object. Independent decryption is then performed using a random-order Hadamard matrix assigned to each object. The proposed method achieves multi-object parallel encryption and independent decryption using a lightweight optical system, with improved efficiency, lower hardware costs, and smaller ciphertext size compared to conventional methods. In addition, it also exhibits robustness against both cropping and noise attacks. These results indicate potential for practical applications and may contribute to future developments in multi-object optical encryption for single-pixel imaging security.
Optical encryption inherently provides strong security advantages, with hybrid optoelectronic systems offering additional degrees of freedom by integrating optical and algorithmic domains. However, existing optical encryption schemes heavily rely on electronic computation, limiting overall efficiency, and the physical keys are susceptible to damage, compromising both security and system stability. To overcome these challenges, we introduce the quasi-periodic optical key (Q-POK), which combines long-range order with short-range disorder, enabling enhanced security and robustness against damage within a single platform. By leveraging diffraction symmetry, our design enables optics-driven encryption, effectively shifting the optoelectronic balance toward photonic processing. Moreover, we innovatively apply deep learning to reconstruct the complex optical ciphertext field using only amplitude data and cryptographic keys, simultaneously achieving data compression and improved security. Within this framework, the key space includes continuously tunable parameters such as wavelength, propagation distance, phase modulation, and Q-POK geometry, significantly expanding cryptographic diversity. Our system also demonstrates robust cryptographic reliability by reducing inter-class distances by over 50% and tolerating up to 20% ciphertext loss. Our framework represents a generation of physically grounded, algorithmically enhanced optical cryptosystems—laying a foundational pathway for scalable, hardware-integrated information security paradigms.
Optical encryption inherently provides strong security advantages, with hybrid optoelectronic systems offering additional degrees of freedom by integrating optical and algorithmic domains. However, existing optical encryption schemes heavily rely on electronic computation, limiting overall efficiency, while the physical keys are susceptible to damage, compromising both security and system stability. To overcome these challenges, we introduce the Quasi Periodic Optical Key (QPOK), which combines long range order with short range disorder, enabling enhanced security and robustness against damage within a single platform. By leveraging diffraction symmetry, our design enables optics-driven encryption, effectively shifting the optoelectronic balance toward photonic processing. Moreover, we innovatively apply deep learning to reconstruct the complex optical ciphertext field using only amplitude data and cryptographic keys, simultaneously achieving data compression and improved security. Within this framework, the key space includes continuously tunable parameters such as wavelength, propagation distance, phase modulation, and Q-POK geometry, significantly expanding cryptographic diversity. Our system also demonstrates robust cryptographic reliability by reducing inter-class distances by over 50% and tolerating up to 20% ciphertext loss. Our framework represents a new generation of physically grounded, algorithmically enhanced optical cryptosystems, laying a foundational pathway for scalable, hardware-integrated information security paradigms.
In the age of information explosion, the conventional optical communication protocols are rapidly reaching the limits of their capacity, as almost all available degrees of freedom (e.g., wavelength, polarization) for division multiplexing have been explored to date. Recent advances in coherent mode division multiplexing have greatly facilitated high-speed optical communications and secure, high-capacity information storage and transfer. However, coherent mode division multiplexing is quite vulnerable to even minute environmental disturbances which can cause significant information loss. Here, we propose and experimentally demonstrate a paradigm shift to incoherent mode division multiplexing for high-security optical information encryption by harnessing the degree of coherence of structured random light beams. In contrast to the conventional techniques, our approach does not require mode orthogonality to circumnavigate unwanted mode crosstalk. In addition, our protocol has, in principle, no upper bound on its capacity. Thanks to the extreme robustness of structured random light to external perturbations, we are able to achieve highly accurate information encryption and decryption in the adverse environment. The proposed protocol opens new horizons in an array of fields, such as optical communications and cryptography, and it can be relevant for information processing with acoustical, matter as well as other types of waves.
As we enter the big data and artificial intelligence (AI) era, integrating security and communication over optical fiber has become a critical challenge. This urgency is driven by the need to protect vast amounts of sensitive data, ensuring privacy security across global high-capacity optical networks. Traditional secure communication methods often struggle to maintain high-capacity transmission performance while providing robust security. Here we propose an integrated encryption and communication (IEAC) framework, designed to maximize mutual information (MI) for legal users while minimizing it for potential eavesdroppers. Enabled by end-to-end deep learning, this holistic framework trains a random number-selected geometric constellation shaping scheme to optimize encryption processes and transmission quality simultaneously. The IEAC experiment system achieves a groundbreaking single-channel transmission rate of 1 Terabit per second (Tb/s) over a 1200-km fiber link, employing a 26-channel, 3.9 THz bandwidth, full C-band wavelength division multiplexing (WDM) configuration. The MI for eavesdroppers is under 0.2 bit per symbol where the regular value is near 4.0, ensuring secure transmission. The IEAC scheme offers a scalable, promising solution to meet the escalating demand for high-throughput, secure data transmission in the face of advancing big data and AI computational technologies.