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Optics Express

Deep-learning-based cross-talk free and high-security compressive encryption with spatially incoherent illumination

Yi Qin, Yuhong Wan, Qiong Gong, Minghua Zhang

Published Feb 22, 2023• 13 citations
Publisher

Abstract

Incoherent optical cryptosystem is promising for its immunity against coherent noise and insensitivity to misalignment, and compressive encryption is desirable considering the increasingly demand on the exchange of encrypted data via Internet. In this paper, we propose a novel optical compressive encryption approach with spatially incoherent illumination based on deep learning (DL) and space multiplexing. For encryption, the plaintexts are individually sent to the scattering-imaging-based encryption (SIBE) scheme where they are transformed to scattering images with noise appearances. Afterwards, these images are randomly sampled and then integrated into a single package (i.e., ciphertext) by space multiplexing. The decryption is basically the inverse of the encryption, while it involves an ill-posed problem (i.e., recovering the noise-like scattering image from its randomly sampled version). We demonstrated that such a problem can be well resolved by DL. The proposal is radically free from the cross-talk noise existing in many current multiple-image encryption schemes. Also, it gets rid of the linearity bothering the SIBE and is hence robust against the ciphertext-only attack based on phase retrieval algorithm. We present a series of experimental results to confirm the effectiveness and feasibility of the proposal.

DOI
10.1364/oe.483136

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Incoherent optical cryptosystem is promising for its immunity against coherent noise and insensitivity to misalignment, and compressive encryption is desirable considering the increasingly demand on the exchange of encrypted data via Internet. In this paper, we propose a novel optical compressive encryption approach with spatially incoherent illumination based on deep learning (DL) and space multiplexing. For encryption, the plaintexts are individually sent to the scattering-imaging-based encryption (SIBE) scheme where they are transformed to scattering images with noise appearances. Afterwards, these images are randomly sampled and then integrated into a single package (i.e., ciphertext) by space multiplexing. The decryption is basically the inverse of the encryption, while it involves an ill-posed problem (i.e., recovering the noise-like scattering image from its randomly sampled version). We demonstrated that such a problem can be well resolved by DL. The proposal is radically free from the cross-talk noise existing in many current multiple-image encryption schemes. Also, it gets rid of the linearity bothering the SIBE and is hence robust against the ciphertext-only attack based on phase retrieval algorithm. We present a series of experimental results to confirm the effectiveness and feasibility of the proposal.
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.
Abstract Exclusive-OR (XOR) operation is a popular technique in optical cryptography. The linear and inverse properties of XOR operation provide a simple way of encryption but in some cases fail to provide strong security. In XOR-based image encryption, each pixel is individually encrypted, therefore secret information can be traced with partial knowledge of the key. In this paper, we describe a simple and practical method to improve the strength and effectiveness of XOR-based encryption. A higher level of security is achieved by implementing a phase retrieval algorithm with XOR operation. Another advantage of the proposed scheme is that the optical XOR operation is demonstrated using incoherent light sources, which make the system compact, speckle free, and cost effective. Also, to overcome the problem of quality degradation while decrypting, quick response code-based ciphertext has been implemented. Both simulation and experimental results are demonstrated as a proof-of-concept.
We report a simultaneous image compression and encryption scheme based on solving a typical optical inverse problem. The secret images to be processed are multiplexed as the input intensities of a cascaded diffractive optical system. At the output plane, a compressed complex-valued data with a lot fewer measurements can be obtained by utilizing error-reduction phase retrieval algorithm. The magnitude of the output image can serve as the final ciphertext while its phase serves as the decryption key. Therefore the compression and encryption are simultaneously completed without additional encoding and filtering operations. The proposed strategy can be straightforwardly applied to the existing optical security systems that involve diffraction and interference. Numerical simulations are performed to demonstrate the validity and security of the proposal.
This work reports an optical double-image crosstalk free encryption scheme that employs equal modulus decomposition and random masks. For the encryption, two plaintexts by a random amplitude mask and a random phase mask have been encrypted into a single ciphertext mask and two private key masks. Owing to the two random masks introduced, the functional relation between the plaintext pair and the ciphertext indirectly cause the paucity of constraints employed for the specific attack. Unlike the traditional phase-truncation-based techniques, this scheme is immune to the information leakage and different types of attacks. Furthermore, the three different diffraction distances and the illuminating wavelength also function as four additional keys to significantly reinforce the security. Simulation results demonstrate the feasibility and validity of the proposal.
Providing secure and efficient transmission for multiple optical images has been an important issue in the field of information security. Here we present a hybrid image compression, encryption and reconstruction scheme based on deep learning-assisted single-pixel imaging (SPI) and orthogonal coding. In the optical SPI-based encryption, two-dimensional images are encrypted into one-dimensional bucket signals, which will be further compressed by a binarization operation. By overlaying orthogonal coding on the compressed signals, we obtain the ciphertext that allows multiple users to access with the same privileges. The ciphertext can be decoded back to the binarized bucket signals with the help of orthogonal keys. To enhance reconstruction efficiency and quality, a deep learning framework based on DenseNet is employed to retrieve the original optical images. Numerical and experimental results have been presented to verify the feasibility and effectiveness of the proposed scheme.
In this paper, a new multiple-image encryption and decryption technique that utilizes the compressive sensing (CS) concept along with a double-random phase encryption (DRPE) has been proposed. The space multiplexing method is employed for integrating multiple-image data. The method, which results in a nonlinear encryption system, is able to overcome the vulnerability of classical DRPE. The CS technique and space multiplexing are able to provide additional key space in the proposed method. A numerical experiment of the proposed method is implemented and the results show that the proposed method has good accuracy and is more robust than classical DRPE. The proposed system is also employed against chosen-plaintext attacks and it is found that the inclusion of compressive sensing enhances robustness against the attacks.