Experimental study on optical image encryption with asymmetric double random phase and computer-generated hologram

Xi, Sixing; Wang, Xiaolei; Song, Lipei; Zhu, Zhuqing; Zhu, Bowen; Huang, Shaobin; Yu, Ning; Wang, Huaying

doi:10.1364/oe.25.008212

Cited by 57 publications

(33 citation statements)

References 23 publications

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“…Holography has captivated us with its stunning visual effects, finding applications in augmented reality, medical imaging, laser multibeam projection, beam shaping, interference measurement, optical manipulation, and anticounterfeiting . By manipulating the phase or amplitude of light as it passes through the plane of the hologram, arbitrary grayscale images can be projected in the far field.…”

Section: Introductionmentioning

confidence: 99%

Off‐Axis Holography with Uniform Illumination via 3D Printed Diffractive Optical Elements

Wang

Liu

Ruan

et al. 2019

Advanced Optical Materials

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hologram (CGH) algorithms, such as the algorithms of Gerchberg-Saxton (GS), [14] Yang-Gu, [15] Fienup, [16] and Simulated Annealing. [17][18][19] Diffractive optical elements (DOEs) are a common application of CGH. In particular, DOEs consisting of square phase elements (i.e., pixels) are the easiest to design and fabricate. Each of these elements is a structure with a discrete height or refractive index designed to locally modulate the phase of the transmitted light. When combined, DOEs with diffraction efficiencies as high as 80% can be routinely achieved. [20] DOEs inevitably suffer from the zero order spot that appears as a bright spot in the middle of the projected image. The projected image corresponds to the intensity distribution in the Fourier plane, which is obtained by Fourier transform (FT) of the modified wavefront immediately after the hologram plane. Hence, the zero order spot is also referred to as the DC noise. This bright spot is exacerbated by fabrication imperfections and illumination beyond the extent of the DOE. [20][21][22] For instance, a commercialized liquid crystal spatial light modulator (SLM) with a filling fact or of ≈90% would result in a zero order spot due to light that passes through the dead regions. [23] Transparent dielectric structures fabricated by etching and polymer structure made by lithography would possess defects in the surface topography [11,24] that lead to the zero order spot. Furthermore, the inhomogeneity and dispersive optical property of the phase element materials can impede the performance of DOEs. [25] Ineluctably, a bright zero order spot appears in the center of the Fourier plane, [22,25] Diffractive optical elements (DOEs) provide a compact and energy-efficient solution to project arbitrary grayscale images onto a distant screen. Unfortunately, they invariably suffer from the zero order spot, which is caused mainly by undiffracted light that travels along the optical axis of an illuminating laser beam. To produce projected images without the bright spot, one can either shift the intended projection off-axis or block the zero order. However, images projected by these methods are occluded by the dark fringes of the diffraction pattern ("shadowing" effect) or increase the complexity of the optical setup. Here, a new type of DOE is introduced with blazed facets to shift the laser power into the off-axis direction. By adding blazed facets onto each phase element of a computer-generated hologram, far-field projections that are free of both the zero order spot and shadowing effects are produced while maintaining a diffraction efficiency as high as 86%. The blazed facets are fabricated by 3D direct laser writing, which enables continuous phase modulation within a single pixel. This concept of sub-pixel level modification of diffractive optical elements can be extended to other applications requiring precise wavefront shaping or detection, such as 3D displays, mixed-reality technology, and optical analog computing.

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Section: Introductionmentioning

confidence: 99%

Off‐Axis Holography with Uniform Illumination via 3D Printed Diffractive Optical Elements

Wang

Liu

Ruan

et al. 2019

Advanced Optical Materials

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“…In addition, optical encryption systems based on imaging mechanisms [8,14,28,29], such as ghost imaging, diffractive imaging and interferometric imaging, are illustrated to be applicable for securing information. It is also found that computer-generated hologram (CGH) [30][31][32][33][34][35] can be applied for optical encryption, and its remarkable advantages, e.g., simple implementations, have been explored for practical applications. In the CGH-based optical encryption, the input image can be iteratively or non-iteratively encoded into one or several phase-only masks (i.e., CGH) [31][32][33][34][35].…”

Section: Introductionmentioning

confidence: 99%

Learning-based attacks for detecting the vulnerability of computer-generated hologram based optical encryption

Zhou¹,

Xiao²,

Chen³

2020

Opt. Express

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Optical encryption has attracted wide attention for its remarkable characteristics. Inspired by the development of double random phase encoding, many researchers have developed a number of optical encryption systems for practical applications. It has also been found that computer-generated hologram (CGH) is highly promising for optical encryption, and the CGH-based optical encryption possesses remarkable advantages of simplicity and high feasibility for practical implementations. An input image, i.e., plaintext, can be iteratively or non-iteratively encoded into one or several phase-only masks via phase retrieval algorithms. Without security keys, it is impossible for unauthorized receivers to correctly extract the input image from ciphertext. However, cryptoanalysis of CGH-based optical encryption systems has not been effectively carried out before, and it is also concerned whether CGH-based optical encryption is sufficiently secure for practical applications. In this paper, learning-based attack is proposed to demonstrate the vulnerability of CGH-based optical security system without the direct retrieval of optical encryption keys for the first time to our knowledge. Many pairs of the extracted CGH patterns and their corresponding input images (i.e., ciphertext-plaintext pairs) are used to train a designed learning model. After training, it is straightforward to directly retrieve unknown plaintexts from the given ciphertexts (i.e., phase-only masks) by using the trained learning model without subsidiary conditions. Moreover, the proposed learning-based attacks are also feasible and effective for the cryptoanalysis of CGH-based optical security systems with multiple cascaded phase-only masks. The proposed learning-based attacking method paves the way for the cryptoanalysis of CGH-based optical encryption.

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“…To improve its security, the DRPE is extended to different domains such as fractional Fourier domain [9], Fresnel domain [10], Gyrator domain [11], and Hartley domain [12]. Other strategies, such as interference-based encryption [13]- [15], computer-generated hologram-based optical encryption [16], [17], and computational ghost image encryption [18]- [21] have also been proposed for higher security encryption. With the emergence of cryptanalysis of cryptosystems, researchers have successively proposed asymmetric encryption approaches.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, the asymmetric cryptosystems show resistance to various attacks on account of the existence of private key and public key. Subsequently, researchers successively propose improved asymmetric cryptosystems [17], [30]- [37] due to its significant asymmetric characteristics.…”

Section: Introductionmentioning

confidence: 99%

Resolution Adaptative Network for Cryptanalysis of Asymmetric Cryptosystems

Wang

et al. 2020

IEEE Access

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The asymmetric optical cryptosystems have been widely concerned due to their prominent characteristics of high security and robustness against attacks. In this paper, a resolution adaptative network is proposed to attack the asymmetric optical cryptosystems, which solves the issue of requiring a lot of experiments to change the network structure and parameters for effectively attacking to ciphertexts with different resolutions. The proposed network of fixing the network structure and parameters can be trained by inputting plaintext-ciphertext pairs with different resolutions, and then the trained network model can generate the retrieved plaintexts with corresponding resolutions. Numerical simulation and analysis show that the classical asymmetric optical cryptosystems can be attacked by the proposed network successfully. Moreover, the excellent resolution adaptability of the proposed network is verified by training and testing the images with different resolutions. Furthermore, the generalization ability and robustness of the proposed network is verified. In general, the issue of the input resolution adaptability of the cryptanalysis network is addressed firstly to our best knowledge. INDEX TERMS Resolution adaptative network, asymmetric cryptosystems, cryptanalysis.

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Experimental study on optical image encryption with asymmetric double random phase and computer-generated hologram

Cited by 57 publications

References 23 publications

Off‐Axis Holography with Uniform Illumination via 3D Printed Diffractive Optical Elements

Off‐Axis Holography with Uniform Illumination via 3D Printed Diffractive Optical Elements

Learning-based attacks for detecting the vulnerability of computer-generated hologram based optical encryption

Resolution Adaptative Network for Cryptanalysis of Asymmetric Cryptosystems

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