Optical multiple information hiding via azimuth multiplexing

Lv, Wenjin; Sun, Xinkai; Yang, Dongyu; Zhu, Yi; Tao, Ye; Shi, Yishi

doi:10.1016/j.optlaseng.2021.106574

Cited by 13 publications

(8 citation statements)

References 34 publications

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“…Figure 7 Compared with conventional Unet and convolution neural network (CNN), the proposed DenseNet has more direct connections between layers, strengthening feature propagation, encouraging feature reuse and substantially reducing the number of parameters. The previously proposed neural networks (CNN and Resnet) [20][21][22] have been further used to attack the two types of NOCs. However, the results obtained under the same training conditions, i.e., the same quantity of data, train-ing time and epoch, are not satisfactory.…”

Section: Numerical Experiments and Discussionmentioning

confidence: 99%

“…Owing to their nonlinear characteristics, it is reasonable to use deep neural networks to estimate the relationship described by Eqs. ( 21) and (22). In our proposed method, the proposed DenseNet is designed to achieve the approximate equivalent models of NOCs by using a number of "plaintext-ciphertext" pairs.…”

Section: Densenet Architecture Designed For Cryptanalysismentioning

confidence: 99%

“…[6] Since the DRPE-based optical encryption has high flexibility and expansion capability, consequently, many other optical encryption methods have also been developed, which proves to be feasible and effective. [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25] In recent years, the vulnerability analysis of optical encryption systems has attracted wide interest from researchers. The DRPE-based optical encryption schemes have been verified to be vulnerable to different kinds of attacks [26][27][28][29] due to its inherent properties of linearity and symmetry.…”

Section: Introductionmentioning

confidence: 99%

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Deep-learning-based cryptanalysis of two types of nonlinear optical cryptosystems

Wang¹,

Wei²

2022

Chinese Phys. B

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The two types of nonlinear optical cryptosystems (NOCs) that are respectively based on amplitude-phase retrieval algorithm (APRA) and phase retrieval algorithm (PRA) have attracted a lot of attention due to their unique mechanism of encryption process and remarkable ability to resist common attacks. In this paper, for the first time, to the best of our knowledge, the security of the two types NOCs is evaluated by using a deep-learning (DL) method, wherein an end-to-end densely connected convolutional network (DenseNet) model for cryptanalysis is developed. The proposed DL-based method is able to retrieve unknown plaintexts from the given ciphertexts by using the trained DenseNet model without a prior knowledge of any public or private keys. The results of numerical experiments with the DenseNet model clearly demonstrate the validity and good performance of the proposed the DL-based attack on NOCs.

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Section: Numerical Experiments and Discussionmentioning

confidence: 99%

Section: Densenet Architecture Designed For Cryptanalysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Deep-learning-based cryptanalysis of two types of nonlinear optical cryptosystems

Wang¹,

Wei²

2022

Chinese Phys. B

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“…A visually secure encryption algorithm for images combining parallel compression perception and integer wavelet domain embedding is designed in the literature [7]. In order to resist security attacks on images during transmission, scholars have proposed many schemes for hiding image, such as optical systems [8], deep learning [9], etc.…”

Section: Introductionmentioning

confidence: 99%

Image hiding via compressed sensing and frequency domain transform

Xing¹,

Wu²

2023

International Conference on Signal Processing and Communication Technology (SPCT 2022)

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In this paper, a transform domain information hiding algorithm with visual security based on compressed sensing (CS) is proposed. To increase the security, an improved coupled map lattices is used for keystream and measurement matrix generation. To save the storage space, the semi-tensor product is applied to the measurement matrix. Using the image transform domain property, the compressed and encrypted image to be hidden is embedded into the high-frequency part of the carrier image through mathematical operations, and then the carrier image is inverted to finally form a visually secure image. Simulation results and performance analysis show that the designed information hiding scheme has better hiding effect and high security.

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“…To improve the security performance, incoherent optical cryptosystem is combined with other security enhancement techniques, such polarized encoding [14], QR code [15][16], and aperture encoding [17]. And except for the frosted glass, phase liquid-crystal spatial light modulator (SLM) and diffractive optical element (DOE) are alternative to be the encoding element [18][19]. When liquid-crystal SLM or DOE are used, the phase distribution of the mask can be designed according to the user demand.…”

Section: Introductionmentioning

confidence: 99%

Incoherent optical cryptosystem based on hybrid wave aberration

Ji,

Chang,

Yang

et al. 2023

Optical Design and Testing XIII

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An incoherent optical cryptosystem based on hybrid wave aberration is proposed in this study. The proposed cryptosystem is designed with different channels to divide the object. In each channel, different wave aberrations are allocated to form the hybrid wave aberration. When the object is imaged by the channel with huge wave aberrations, its corresponding image will be blurry enough to form a ciphertext. Because the different wave aberrations in different channels can be regarded as the key, the proposed optical cryptosystem can achieve multi-key encryption as well as local encryption. The proposed optical cryptosystem enhances the security of incoherent optical cryptosystem through the quantity of keys and the special construction method of ciphertext.

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Optical multiple information hiding via azimuth multiplexing

Cited by 13 publications

References 34 publications

Deep-learning-based cryptanalysis of two types of nonlinear optical cryptosystems

Deep-learning-based cryptanalysis of two types of nonlinear optical cryptosystems

Image hiding via compressed sensing and frequency domain transform

Incoherent optical cryptosystem based on hybrid wave aberration

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