In this manuscript, we have proposed an asymmetric encryption-cum-authentication algorithm based on computational ghost imaging using QZ Synthesis method in the Gyrator domain. Computational ghost imaging enables to store image information in a single pixel by reconstructing images using light intensity correlations from random patterns. It provides high security and reduces vulnerability to tampering, making it ideal for secure imaging applications. Gyrator transform and QZ Synthesis provides additional encryption keys to the cryptosystem. QZ Synthesis method used for combining two images and produce a single ciphertext in the proposed cryptosystem. Two distinct types of input images are used to validate the proposed encryption-cumauthentication algorithm. To quantify the encryption quality, we utilized assessment based on critical parameters, including pixel correlation coefficients and entropy measurements to ensure high degree of randomness in ciphertext. The algorithm's resistance to statistical attacks is further illustrated through 3D results and pixel distribution mapping, along with numerical validation including mean squared error to confirm minimal information leakage. The results indicate that the proposed algorithm effectively resist statistical and basic cryptographic attacks. Every decryption key is crucial for accurately reconstructing the original image. Therefore, the proposed authentication algorithm ensures high security.

To address the escalating need for secure and efficient multimedia transmission and optimized data storage, this paper proposes a robust double-phase image encryption and compression framework that integrates decomposition techniques within the Gyrator transform domain. In the proposed scheme, input images are converted into phase images and QZ synthesis is then utilized to fuse these images, generating highly secure, independent key components. These synthesized components are mapped into the Gyrator domain, whose additional rotational degree of freedom and strong parameter sensitivity provide improved security and encoding flexibility over conventional Fourier and fractional Fourier transform-based methods. To achieve efficient data handling, the transformed data undergoes truncated singular value decomposition. This step extracts structured components that facilitate concurrent encryption and compression, ensuring that the ciphertext is secure and compact. Upon decryption the input images are recovered with high accuracy as evidenced by the statistical metrics: MSE, PSNR, CC and SSIM. The truncated parameter k provides flexibility to control the trade-off between compression efficiency and reconstruction quality. The integration of these multi-domain operations results in a significantly enlarged key space and enhances resistance against brute-force, statistical, differential and basic cryptographic attacks. Numerical simulation results confirm that the proposed scheme maintains high compression efficiency without compromising the reconstruction fidelity. Robustness of the scheme is also evident from its endurance of noise and occlusion attacks.

With the exponential growth of digital communication channels, the transmission and storage of high-dimensional multimedia data, including images and videos, have become crucial to modern information systems. The areas like defense, healthcare and banking utilize the modern communication channels very often to share information. Thus, ensuring the confidentiality, integrity, and authenticity of sensitive visual information has become a critical challenge. Although there are various conventional data security algorithms that exist, they often encounter limitations in handling large-scale image data due to high computational complexity and slow processing speed. Optical cryptosystems have emerged as a promising alternative owing to their inherent parallelism, multidimensional processing capability, large key space, and high-speed implementation. In this review, recent advancements in optical cryptosystems beyond classical DRPE scheme are summarized. Particularly, we examine the asymmetric optical cryptosystems based on PTFT, QZ decomposition, QZ synthesis, SVD, GSVD, interference, and computer-generated holography. Moreover, this review also discussed the emerging approaches of optical data security using structured light beams such as vector vortex beams. Finally, the review covered various techniques to test the vulnerabilities of optical cryptosystems such as plaintext and modified plaintext attacks, AI based cryptographic attacks, and iterative attacks designed for asymmetric cryptosystems. The objective of this review article is to serve as a reference text for readers from a variety of research backgrounds interested in the domain of optical information security.

A secure cryptosystem based on improved version of Yang–Gu algorithm has been proposed along with lower–upper (LU) decomposition for compression in gyrator transform. Yang–Gu algorithm introduces nonlinearity whereas LU decomposition leads to compression in the proposed scheme. Two random phase masks and binary phase modulators are used in the encryption process. Random phase masks act as public keys and binary phase modulations are applied to generate private keys. Grayscale and medical images are used to validate the proposed cryptosystem against different types of attacks. The statistical attack including information entropy, histogram analysis, correlation distribution plots, and 3-D plots are analyzed for the robustness of the proposed scheme. The quality of the retrieved image is compared with original image using the value of the correlation coefficient. The proposed scheme also showed resistance against data shuffling attack and basic attacks. Key sensitivity analysis demonstrated that the scheme is highly sensitive to its private keys and gyrator transform parameters. Therefore, based on above discussed results, the proposed scheme enhances the security.

In this manuscript, an authentication algorithm based on three phase only masks on interference algorithm using elliptic curve cryptography and sparsification in the fractional Hartley domain is proposed. The proposed algorithm strengthens the security of three POMs-based interference algorithms which are vulnerable to iterative cryptographic attacks. The cascaded use of fractional Hartley transform and interference algorithm contributes to a larger keyspace in the proposed cryptosystem. The efficacy and robustness of the proposed authentication algorithm is validated through simulations on binary and grayscale images. The proposed authentication method was tested using multiple statistical analyses, such as correlation coefficients, entropy calculations, error metrics, distribution assessments, and visual representations like mesh plots and histogram. To access its robustness, the cryptosystem was evaluated in the presence of practical disturbances like noise. Moreover, the security of the proposed cryptosystem is also tested against available iterative and plaintext based cryptographic attacks. Experimental results demonstrate the security of the proposed cryptosystem, making it viable for authentication.

This study examines video encryption using the well-established optical technique of double random phase encoding (DRPE). We first divide the input video into individual frames and apply the DRPE method to each frame separately. To assess the security of DRPE in video encryption, a chosen-plaintext attack is performed, exposing its vulnerabilities in handling video data. To enhance encryption security, we propose a novel scheme that integrates elliptic curve-based pixel scrambling with DRPE. In this approach, structured phase masks derived from a devil's vortex toroidal lens (DVTL) are employed instead of traditional random phase masks. The use of DVTL-based structured phase masks resolves the axis alignment issues typically encountered in optical setups. The new algorithm is validated with grayscale, medical, and binary videos, with its implementation carried out digitally in MATLAB R2023b. Frame analysis was performed using visual tools such as histograms and 3D plots. The scheme's effectiveness is measured using various metrics, including information entropy, mean squared error, peak signal-to-noise ratio, correlation coefficient, and structural similarity index measure. Additionally, the scheme's sensitivity to encryption keys such as elliptic curve parameters has been tested, and its resistance to occlusion attacks has been evaluated. The proposed approach's susceptibility to cryptographic attacks such as chosen-plaintext attacks has also been thoroughly analysed.

This manuscript introduces the Bird wing map, a nonlinear discrete chaotic system, analysed using bifurcation diagrams, Lyapunov exponents, and chaos decision trees. Its dynamical properties, including fixed points and stability, are examined theoretically. The dynamical characteristics of the Bird wing map are explored, including its fixed points and stability analysis. In addition to theoretical exploration, an image encryption algorithm exemplifying the practical applications of the Bird wing map is demonstrated. This encryption algorithm is based on the phase truncation algorithm in the Fresnel domain. The Bird wing map permutes pixels, and its parameters serve as encryption and decryption keys in the cryptosystem. Simulations were performed on various types of images, with results presented for the grayscale image Cameraman, binary 'CHAOS', medical and colour images. The proposed algorithm is also tested with basic cryptographic attacks. Results validate that proposed algorithm based on Bird wing map is secure and robust.

We propose a robust optical cryptosystem for securely watermarking and transmitting two-color images by leveraging the fractional Hermite-transform (FrHMT). The method employs elliptic curves, Arnold's cat map, and affine transformation for effective pixel scrambling, whereas vortex lens phase masks enhance key security by expanding the key space and simplifying key distribution. The QZ algorithm merges the two images into a single encrypted output, introducing nonlinearity and enabling efficient transmission, whereas dual-layer protection is achieved by embedding the encrypted data within a host image via watermarking, ensuring covert communication. The process begins by converting input color images into indexed formats via colormap extraction. This step reduces computational complexity while preserving essential color information, making subsequent encryption and watermarking more efficient. The scheme is validated and evaluated through extensive experiments, including histogram analysis, mesh plots, and correlation distribution plots, confirming its resilience against statistical attacks. This system is particularly useful for confidential document transmission and multimedia copyright protection. In addition, a comparative analysis with existing encryption schemes highlights the advantages of the proposed cryptosystem in terms of security and efficiency. (c) 2025 Society of Photo-Optical Instrumentation Engineers (SPIE)

This paper presents an innovative optical asymmetric cryptosystem designed for dual-image encryption, leveraging QZ algorithm and structured phase masks enhanced with vortex and toroidal lenses. The proposed scheme integrates watermarking within the fractional Hermite transform domain to securely embed encrypted data into a host image. Dual-image encryption is achieved through the QZ synthesis process. The system’s performance has been evaluated using medical images for encryption and watermarking. Experimental results demonstrate its robustness against statistical attacks and conventional cryptographic attacks. Furthermore, a detailed sensitivity analysis of critical encryption parameters has been performed to assess system reliability. The proposed approach offers a novel and robust solution for secure dual-image encryption.

This paper introduces a non-linear multi-image asymmetric encryption scheme using Quasinormal-Zernike (QZ) algorithm and Fresnel transform. The method encrypts multiple images into a single ciphertext while ensuring robust security through highly sensitive QZ and Fresnel parameters. The proposed scheme is validated via MATLAB simulations. The scheme demonstrates strong resistance to specific attack, basic cryptographic attacks and statistical attacks, supported by histogram plots, correlation distribution plots, and entropy analysis, along with key performance metrics. The one of the key strength of this approach is its scalability which allows it to extend up to 5n images, offering a versatile solution for multi-image encryption with superior security and efficiency compared to existing methods.

The dimension and size of data is growing rapidly with the extensive applications of computer science and lab based engineering in daily life. Due to availability of vagueness, later uncertainty, redundancy, irrelevancy, and noise, which imposes concerns in building effective learning models. Fuzzy rough set and its extensions have been applied to deal with these issues by various data reduction approaches. However, construction of a model that can cope with all these issues simultaneously is always a challenging task. None of the studies till date has addressed all these issues simultaneously. This paper investigates a method based on the notions of intuitionistic fuzzy (IF) and rough sets to avoid these obstacles simultaneously by putting forward an interesting data reduction technique. To accomplish this task, firstly, a novel IF similarity relation is addressed. Secondly, we establish an IF rough set model on the basis of this similarity relation. Thirdly, an IF granular structure is presented by using the established similarity relation and the lower approximation. Next, the mathematical theorems are used to validate the proposed notions. Then, the importance-degree of the IF granules is employed for redundant size elimination. Further, significance-degree-preserved dimensionality reduction is discussed. Hence, simultaneous instance and feature selection for large volume of high-dimensional datasets can be performed to eliminate redundancy and irrelevancy in both dimension and size, where vagueness and later uncertainty are handled with rough and IF sets respectively, whilst noise is tackled with IF granular structure. Thereafter, a comprehensive experiment is carried out over the benchmark datasets to demonstrate the effectiveness of simultaneous feature and data point selection methods. Finally, our proposed methodology aided framework is discussed to enhance the regression performance for IC50 of Antiviral Peptides.

Fuzzy-rough set (FRS) has been effectively implemented as a powerful pre-processing tool to cope with the issues such as vagueness, imprecision, noise and uncertainty in high-dimensional data analysis. However, FRS fails to handle the uncertainty due to identification, which is very much common in heterogeneous data. Moreover, it is always challenging to handle different issues such as vagueness, uncertainty, and noise during elimination of irrelevant and redundant features. This paper investigates an intuitionistic fuzzy rough set (IFRS)-aided feature selection method by using information entropy notion to tackle these issues simultaneously. We establish an intuitionistic fuzzy (IF) similarity relation. Then IFRS model is discussed based on this relation. Next, we present a novel IF granular structure. Based on the granular structure, we present lambda-conditional entropy for IF framework. Further, relevant mathematical theorems are proved to justify the theoretical aspect of the models. Moreover, a positive region preserved attribute selection method is proposed. A comprehensive experimental study is discussed to demonstrate the effectiveness and practical validation of the proposed method. Finally, a methodology is developed based on proposed models, which increases accuracy for the minority RNA silencing suppressors against majority class non-suppressors as evident from better sensitivity and G-means metrics.

In the modern era, the secure transmission and storage of information are among the utmost priorities. Optical security protocols have demonstrated significant advantages over digital counterparts, i.e., a high speed, a complex degree of freedom, physical parameters as keys (i.e., phase, wavelength, polarization, quantum properties of photons, multiplexing, etc.) and multi-dimension processing capabilities. This paper provides a comprehensive overview of optical cryptosystems developed over the years. We have also analyzed the trend in the growth of optical image encryption methods since their inception in 1995 based on the data collected from various literature libraries such as Google Scholar, IEEE Library and Science Direct Database. The security algorithms developed in the literature are focused on two major aspects, i.e., symmetric and asymmetric cryptosystems. A summary of state-of-the-art works is described based on these two aspects. Current challenges and future perspectives of the field are also discussed.

Fuzzy rough entropy established in the notion of fuzzy rough set theory, which has been effectively and efficiently applied for feature selection to handle the uncertainty in real-valued datasets. Further, Fuzzy rough mutual information has been presented by integrating information entropy with fuzzy rough set to measure the importance of features. However, none of the methods till date can handle noise, uncertainty and vagueness simultaneously due to both judgement and identification, which lead to degrade the overall performances of the learning algorithms with the increment in the number of mixed valued conditional features. In the current study, these issues are tackled by presenting a novel intuitionistic fuzzy (IF) assisted mutual information concept along with IF granular structure. Initially, a hybrid IF similarity relation is introduced. Based on this relation, an IF granular structure is introduced. Then, IF rough conditional and joint entropies are established. Further, mutual information based on these concepts are discussed. Next, mathematical theorems are proved to demonstrate the validity of the given notions. Thereafter, significance of the features subset is computed by using this mutual information, and corresponding feature selection is suggested to delete the irrelevant and redundant features. The current approach effectively handles noise and subsequent uncertainty in both nominal and mixed data (including both nominal and category variables). Moreover, comprehensive experimental performances are evaluated on real-valued benchmark datasets to demonstrate the practical validation and effectiveness of the addressed technique. Finally, an application of the proposed method is exhibited to improve the prediction of phospholipidosis positive molecules. RF(h2o) produces the most effective results till date based on our proposed methodology with sensitivity, accuracy, specificity, MCC, and AUC of 86.7%, 90.1%, 93.0% , 0.808, and 0.922 respectively.

In this paper, a multiuser medical image encryption algorithm is proposed. The proposed algorithm utilizes polar decomposition, which enables multiuser features in the proposed algorithm. A computer-generated hologram (CGH) improves the security of the proposed algorithm in the gyrator domain. The phase-only CGH-based multiuser algorithm offers advantages such as storing a large amount of information in a compact space, resistance to counterfeiting, and enhanced security. The proposed method is validated with various statistical metrics, such as information entropy, mean squared error, correlation coefficient, histogram, and mesh plots. Results confirm that the proposed algorithm is secure and robust against potential attacks, such as plaintext attacks, iterative attacks, and contamination attacks. The proposed method has a large keyspace, which makes it very difficult to be breached in real-time with existing computational power.

In this paper, we have proposed an asymmetric image encryption scheme based on phase only computer generated hologram (CGH), QZ synthesis (QZS) method and Umbrella map. In the proposed algorithm, Umbrella map is used for pixel scrambling in fractional Hartley domain (FrHT)whereas CGH and QZS are employed in Fresnel domain (FrT). The proposed scheme establishes the fact that phase-only computer-generated hologram-based encryption algorithms offer advantages such as the ability to store a large amount of information in a compact space, resistance to counterfeiting, and high security. In the proposed algorithm, Umbrella map provides the additional key to the cryptosystem and QZS provides the plaintext based decryption keys that make it asymmetric. The proposed encryption scheme is validated for grayscale and binary image. The statistical strength of the proposed algorithm is evaluated using information entropy, correlation coefficient, 3-D plots, correlation distribution plots and histogram analysis. The proposed encryption algorithm is robust against all statistical attacks and has also been shown to be robust against contamination attacks. The proposed encryption algorithm is also evaluated against basic cryptographic attacks. The results indicate the effectiveness and robustness of the proposed encryption algorithm to make it a secure cryptosystem.

In this manuscript, we proposed a watermarking algorithm based on phase-only computer-generated holography (CGH) in the fractional Hartley domain for digital imaging and communications in medicine (DICOM) images. The proposed algorithm improves the security of the CGH-based algorithm. The cascaded use of fractional Hartley transform and attenuation factor beta increases the keyspace of the proposed watermarking algorithm. The robustness and effectiveness of the proposed watermarking algorithm is validated using simulations on DICOM images. The effectiveness of the proposed watermarking algorithm is assessed using statistical tools in terms of mean-squared error, information entropy, correlation coefficient, histogram, and mesh plots. The robustness is evaluated by testing the proposed algorithm's performance under real-time threats, including contamination and data loss attacks. Furthermore, the security of the proposed algorithm is also tested for existing cryptographic attacks, such as chosen-plaintext attacks, and known-plaintext attacks. The simulation results indicate that the proposed watermarking algorithm is robust and effective.

In this manuscript, an image encryption cum authentication method is proposed. The proposed method utilizes the fingerprint-generated phase mask along with the sparse separation approach, and computer-generated hologram to encrypt the information in Fresnel domain. The Phase only computer-generated holography based authentication algorithm provides multiple benefits, including to store substantial information in compact form, improved security, and strong resistance to counterfeiting. Sparse separation is used for authentication with only thirty percent of the data. The proposed authentication algorithm is evaluated through a range of statistical metrics, including mean squared error, information entropy, correlation coefficient along with histogram, and mesh plot analysis. The results affirm that the proposed cryptosystem is secure and resilient against different types of potential threats, including iterative attacks, plaintext attacks, and contamination attacks. Proposed authentication algorithm has vast key space which makes it challenging to breach in real-time with existing computational capabilities.

This paper presents an asymmetric enciphering technique for binary and greyscale images that uses amplitude and phase truncation operation in fractional Fourier domain. Affine transform is used to introduce randomness for additional security, and to resist specific attack recently mounted on asymmetric schemes. The scheme is validated for binary and greyscale images in MATLAB. The affine transform parameter and the orders of fractional Fourier transform serve as encryption keys in addition to two private keys of asymmetric cryptosystem. To check the efficacy of the scheme, keys sensitivity has been analysed. The scheme is also analysed against occlusion and noise attacks. Other usual attacks and the specific attack on the scheme are also discussed.

In this paper, we have proposed asymmetric image encryption cum authentication cryptosystem based on double random modulus decomposition using computational ghost imaging in the Fourier domain. The literature demonstrates that image encryption algorithms relying on double random modulus decomposition are susceptible to iterative cryptographic attacks. Computational ghost imaging is used to enhance the security of double random modulus decomposition-based cryptosystem and resistant to iterative cryptographic attack. The encrypted image is quite random and appear noisy and can be used for encryption as well as authentication purpose. The proposed cryptosystem is validated for binary, grayscale and medical images. Various statistical metrics, such as mean squared error, information entropy, and correlation coefficient, are applied to analyse the strength of the cryptosystem. Statistical attacks in terms of correlation distribution plots, 3-D plots are performed on the cryptosystem. The results indicate that the cryptosystem is robust against statistical attacks. All decryption keys are essential for faithful recovery of the original image as well as in the authentication cryptosystem. However, in the authentication cryptosystem, we have shown that if more than 6% of any individual key data are lost, cryptosystem fail to recognise the image. Therefore, the proposed encryption cum authentication cryptosystem is safe and secure.