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Multi-image secret sharing (MSS) scheme for two decoding options by employing universal share is discussed in this manuscript. One decoding option is piling of shares to get a secret image preview and the other option needs computation of shares to get a finer view of the secret image. In the past, universal share-based MSS schemes were presented using the common share. This paper presents a universal share-based MSS scheme which also offers two-in-one decoding. Boolean-based light-weight computation is utilized for lossless recovery of secret images. The proposed scheme encodes n secret images into a pie-shaped universal share and n noisy shares. Universal share is a common share for all n secrets; hence, it offers an efficient utilization of the available network bandwidth. Experimental results illustrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

The visual secret sharing (VSS) technique is an encryption model to conceal secret messages into two or more meaningless images, called shares. Information loss is a huge drawback in existing systems. An efficient model has been developed to reconstruct the original image using the Border Shuffled Shepherd Optimization (BSSO) based on the visual cryptography technique. Visual cryptography is performed on the transmitter and receiver sides. At the transmitter side, the input image is partitioned into numerous shares and the B-noisy matrix is optimally generated using BSSO, which is an incorporation of Border Collie Optimization (BCO) and Shuffled Shepherd Optimization (SSO). At the receiver end, all the shares are integrated to reconstruct the original image. The BSSO has maximum Peak-to-Signal Noise Ratio (PSNR) of 56.591, distortion ratio of 0.908, noise level of 0.834, Mean squared error (MSE) of 0.038, and Structural Similarity Index (SSIM) of 0.981, for Lena image. [ABSTRACT FROM AUTHOR]

The use of cloud computing for storing and processing cyber data via the internet has grown widespread in the field of cyber security. Ensuring the secure sharing of cyber data, including texts, images, audio, and video, over the cloud is paramount. However, cloud computing encounters significant challenges concerning cyber data security, authentication, and privacy. The prevailing approaches to data security encounter challenges such as the generation of intricate keys, intensive computation for large keys, and susceptibility to attacks by intruders. Scalability presents its own set of obstacles in maintaining cyber data privacy and ensuring secure communication. A significant privacy concern arises from the frequent changes in membership and data sharing among multiple owners. This paper introduces a novel approach to secure data sharing within data centres by proposing a scheme that employs Private Key Dynamic Visual Cryptography (PK-DVC), Multiple Key Encryption Visual One-Time Pad (MK-VOTP), and visual steganography for encoding and decoding. MK-VOTP is used for data encryption, facilitating data owners' encryption via utilising their identity with supplementary security features. Subsequently, the encrypted data is kept in the cloud, guaranteeing heightened security protocols. Visual steganography is employed for further authentication purposes. Decrypting the original data requires users who fulfil the encrypted properties. This increases security and reduces critical size, allowing several authenticated owners to share data without conflicts. Combining all shares recreates the original picture. The approach described in the paper sounds innovative and addresses several key challenges in ensuring secure data sharing within data centers, particularly in the context of cloud computing. The proposed scheme main components are Private Key Dynamic Visual Cryptography (PK-DVC), Multiple Key Encryption Visual One-Time Pad (MK-VOTP), and Visual Steganography. These three components plays important role in further authenticating the encrypted data or providing additional security measures beyond encryption. By combining these techniques, the proposed scheme aims to provide robust security for sharing cyber data in cloud environments. The use of dynamic keys, multiple encryption layers, and steganography can enhance data security, making it challenging for intruders to access or decipher sensitive information. [ABSTRACT FROM AUTHOR]

Abstract Multi-image secret sharing (MSS) scheme for two decoding options by employing universal share is discussed in this manuscript. One decoding option is piling of shares to get a secret image preview and the other option needs computation of shares to get a finer view of the secret image. In the past, universal share-based MSS schemes were presented using the common share. This paper presents a universal share-based MSS scheme which also offers two-in-one decoding. Boolean-based light-weight computation is utilized for lossless recovery of secret images. The proposed scheme encodes n secret images into a pie-shaped universal share and n noisy shares. Universal share is a common share for all n secrets; hence, it offers an efficient utilization of the available network bandwidth. Experimental results illustrate the effectiveness of the proposed scheme.

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Visual cryptography scheme is initiated to securely encode a secret image into multiple shares. The secret can be reconstructed by overlaying the shares, making it perceptible to the human visual system. Random grid visual cryptography offers key advantages over traditional visual cryptography such as avoiding pixel expansion and the requirement for intricate codebook design. This paper is intended to conduct a critical analysis and implementation of various algorithms in random grid visual cryptography from 2011 to 2022. The focal parameters of this study are theoretical contrast, experimental contrast and visual quality. Experiments were done on binary images for (k, n) algorithms considering different values of threshold. By implementing and analysing the results, the scheme which gives the optimal result is identified. [ABSTRACT FROM AUTHOR]

The undertaking centers around fostering a high level confirmation system to neutralize the developing danger of keylogging assaults. Keylogging, a sort of digital assault that catches keystrokes to take delicate data, represents a huge gamble to conventional confirmation techniques that depend on console input. This undertaking presents an original security approach joining two key developments: a double keypad input framework and a visual verification convention. The double keypad framework comprises of two separate information keypad (Ordinary Keypad and Virtual Keypad), each liable for an alternate part of the validation interaction. This division confuses the capacity for keyloggers to catch total confirmation arrangements, accordingly improving security. At the same time, the visual validation part presents a dynamic, graphical check process that supplements the double keypad framework. Clients interface with visual components like pictures or examples showed on a screen, which are not vulnerable to keylogging. This adds an extra layer of validation that is both easy to use and impervious to information catch by malignant programming. The mix of these two frameworks makes a diverse guard technique. The double keypad component decreases the gamble of compromised keystrokes, while the visual validation process guarantees that regardless of whether keystrokes are caught, the verification stays secure. The venture expects to convey a hearty, secure, and natural verification arrangement that improves assurance against keylogging and other digital dangers, giving a dependable method for getting delicate data in different applications. [ABSTRACT FROM AUTHOR]

In this paper, a (t, n) threshold quantum image secret sharing scheme based on combination theory is proposed. Here, the threshold t is a constant number that should satisfy the condition t ≤ n . In sharing process, the secret image is divided into n shadow images according to n sample matrices constructed by the combination theory and sent to n participants individually. During the recovery process, the original secret image can be fully restored if q (q ≥ t) participants are chosen. However, if the number of chosen participants is less than t, no information about the original secret image can be obtained. The quantum matrix multiplier is first introduced for encryption of the secret images. Then the quantum ⋂ gate is chosen for producing sample matrices. In the recovering steps, we use quantum ⋃ gates to collect shadow images. After that, the quantum circuits of the proposed scheme are given and the complexity of the circuits is discussed. We then conduct numerical simulations of our scheme on grayscale images and RGB images. The results shows that our scheme has a good effect on threshold quantum image secret sharing. [ABSTRACT FROM AUTHOR]

The global growth of the e-commerce industry has heightened concerns among consumers, businesses, and financial institutions regarding fraud while using credit and debit cards and safeguarding personal information. It is necessary to secure information disseminated over insecure channels to prevent unauthorized access. Cryptography and steganography are widely used for this purpose. However, completely relying on the combined usage of both may not be enough in today's world, resulting in weak security. By combining visual cryptography, more levels of security can be added, thus boosting the security of secret information. This study suggests a data security framework that employs multiple levels of security for information. At the first level of security, cryptography is used to encrypt the secret information, and at the second level of security steganography is used to conceal the encrypted text. After that, visual cryptography is applied, which generates the shares of the image obtained. Finally, image steganography is used to hide the generated shares in different color images. When used together, these data security methods greatly improve the secrecy, trustworthiness, and effectiveness of secret messages. The precision of text is determined through Mean Square Analysis (MSE) and correlation coefficient, which involves a comparison of sent and received text. MATLAB environment is used for the implementation. [ABSTRACT FROM AUTHOR]

By splitting a picture into many parts, which, when reassembled, disclose the original image without requiring complicated math, visual cryptography is a strong method for protecting visual information. Problems with pixel enlargement, decreased picture quality, and restricted access structures are common with traditional visual cryptography techniques. Our proposed improved visual cryptography approach incorporates pixel-wise operations and critical access structures to solve these challenges and increase flexibility, picture quality, and security. To reconstruct a picture, our technique calls for building visual cryptographic shares based on critical access structures that specify the exact combinations of shares needed. In order to maintain the image's resolution and reduce pixel expansion, we use pixel-wise processes. By improving the peak signal-to-noise ratio (PSNR) by up to 20% compared to conventional approaches, experimental data show that our strategy greatly improves picture quality. In addition, the suggested approach guarantees that individual shares do not disclose any information on the original picture, thereby maintaining high security requirements. Finally, it is clear that the enhanced visual cryptographic system is well-suited for a wide range of uses in safe communications and data security due to its strong solution for secure picture sharing, increased picture quality, and adjustable access control. [ABSTRACT FROM AUTHOR]

The backdrop: visual cryptography represents a contemporary encryption technology valued for its ease of implementation and comprehensibility, eliminating the need for a secure channel for key transmission and similar requirements. This paper aims: delve into the diverse methods employed in optical encryption, exploring their advantages and drawbacks, with a particular focus on image encryption techniques and the outcomes documented in various research studies. The objective is to identify the strengths and weaknesses inherent in these methodologies, paving the way for potential solutions in the future of optical encryption research. Notably, challenges persist in effectively handling color images and utilizing multiple shares (n, n), impacting both the security and the restoration aspects. The time computation aspects, encompassing creation, encryption, and restoration of these shares, also present challenges. Consequently, ongoing improvements are necessary to address these intricacies and enhance the robustness and applicability of visual cryptography technologies in diverse contexts. [ABSTRACT FROM AUTHOR]

At present, most image encryption schemes directly change plaintext images into ciphertext images without visual significance, and such ciphertext images can be detected by hackers during transmission, and therefore subject to various attacks. To protect the content security and visual safety of images, a learning visual image encryption scheme based on compressed sensing (CS) and cycle generative adversarial network is proposed. First, the secret image is sparse by discrete wavelet transform and compressed by CS. Secondly, the compressed image is permuted and diffused by an improved Henon map to obtain the ciphertext image. Finally, the images are migrated from the ciphertext domain to the plaintext domain by generating an adversarial network to obtain visually meaningful images. We constrain and guide the image generation process by introducing a feature loss function to guarantee the quality of the reconstructed images. Experimental results and security analysis show that the image encryption scheme has sufficient key space, strong key sensitivity, and high reconstruction quality. [ABSTRACT FROM AUTHOR]

Copyright of Baghdad Science Journal is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The day-life calls for transferring millions of images between users, in the era of Information Technology. The security of these images essential using a well-known encryption techniques. The robust image cryptography relies on confusion and diffusion strategies. A new image cryptography algorithm is suggested multiple confusiondiffusion techniques based on 6D hyper chaotic system and Fibonacci Q-matrix. The plain image is confused employing random numbers produced using six- dimension hyper chaotic system across two different confusion phases. In diffusion phases, Fibonacci transformation, XOR operation and cyclic shift are applied. The security of the suggested algorithm is experimented via statistical attacks, differential attacks and brute force attacks. The proposed algorithm is succeeded in passing the security levels, where the key space was expanded to a relatively larger than 10176 and having property of high key sensitivity. The resultant cipher image is free of statistical features by means of histogram and entropy since the histogram is completely equal in all instances even with monochrome colour images. The proposed technique accomplishes 7.99% of average entropy. Furthermore, it showed 99.61% and 31.21 of average NPCR and UACI, respectively. Moreover, the proposed technique records average correlation coefficient values in horizontal, vertical, and diagonal orientations equal to 0.0030, 0.0024, and 0.0026, respectively. [ABSTRACT FROM AUTHOR]

A novel use of visual cryptography is to ensure safe bio-metric authentication in the healthcare industry. The necessity for strong authentication techniques is due to the growing digitization of records and the growing reliance on electronic health systems. There are now a lot of obstacles because of security and privacy issues with conventional bio-metric authentication techniques.Visual cryptography can be done using many algorithms for image encryption. This paper presents a method to encrypt images using two main encryption algorithms: the Advanced Encryption Standard and the Shamir Secret Sharing Scheme. AES, a widely used symmetric encryption algorithm, provides high security by converting plain text to ciphered text using a key which is symmetric. By using the Shamir algorithm, the system creates and saves encrypted images using visual cryptography. In the health care industries, biometric samples are presented as part of the authentication procedure; these samples are divided into shares and encrypted. The shares are subsequently given to the healthcare professionals, who authenticate patients using their unique shares and the help of the central server. By preventing the disclosure of any critical information to a single party, the visual cryptography technology reduces the possibility of data breaches. [ABSTRACT FROM AUTHOR]

Classical experiments using hierarchical stimuli to investigate the ability of capuchin monkeys to integrate visual information based on global or local clues reported findings suggesting a behavioral preference for local information of the image. Many experiments using mosaics have been conducted with capuchin monkeys to identify some of their perceptual phenotypes. As the identification of an image in a mosaic demands the integration of elements that share some visual features, we evaluated the discrimination of shapes presented in solid and mosaic stimuli in capuchin monkeys. Shape discrimination performance was tested in 2 male adult capuchin monkeys in an experimental chamber with a touchscreen video monitor, in three experiments: (i) evaluation of global and local processing using hierarchical stimuli; (ii) evaluation of target detection using simple discrimination procedures; (iii) evaluation of shape discrimination using simple discrimination and delayed matching-to-sample procedures. We observed that both monkeys had preferences for local processing when tested by hierarchical stimuli. Additionally, detection performance for solid and mosaic targets was highly significant, but for shape discrimination tasks we found significant performance when using solid figures, non-significant performance when using circle and square shapes in mosaic stimuli, and significant performance when using Letter X and Number 8 shapes in mosaic stimuli. Our results are suggestive that the monkeys respond to local contrast and partly to global contrast in mosaic stimuli. [ABSTRACT FROM AUTHOR]

Block by block, the secret image will be retrieved from user-friendly and noise-like shares in the Block Based Progressive Secret Sharing (BPVSS) scheme. The majority of existing BPVSS schemes had issues such as schemes that were not appropriate for grayscale and color secret image types, poor contrast in the rebuilt secret image, pixel expansion, more computational power and time required for post processing at the receiver side to recover the secret image, and some schemes that introduced blocking artifact in the rebuilt secret image. To solve the problems described above, we suggested a noise-like and meaningful share generation strategy based on BPVSS and the bit-slicing approach in this study. When compared to previous analogous systems, the proposed method exhibits several benefits, such as (1) it works for both color and grayscale secret images; (2) the contrast of both the rebuilt image and original secret image is exactly the same; (3) there is no pixel expansion issue; (4) the amount of time and computing power required to retrieve the secret image is very low; and (5) there is no blocking artifact issue. With the proposed algorithm for noise-like and meaningful share generation, the average time required to retrieve a secret image of size 256 × 384x3 is 0.1902s and 0.5399 s, respectively. Experimental results show that the suggested system gives better standard performance parameter readings than the BPVSS and Randomized Visual Secret Sharing (RVSS) schemes. [ABSTRACT FROM AUTHOR]

To safeguard the content from malicious devices and users and to provide authentication and security to the transmitted content, it becomes mandatory to devise a combined watermarking and encryption algorithm. This paper addresses this concern by developing an algorithm to authenticate and encrypt the image before transmitting it safely. The algorithm was established using a watermarking technique. The watermarking was done by transforming the image into coefficients and embedding it in high-frequency components. The watermarked image was encrypted using a key generated using a combined logistical tent map and converted to DNA sequences. The sequences are stored and transmitted as such. At the receiver end, the image was recovered and de-watermarked. The label used for the watermark was compared with the obtained watermark at the receiver end. The proposed algorithm conforms to the required CIA triad (confidentiality, integrity, availability). The algorithm was tested for images in the Standard Test images database. On average, for an encrypted image, the peak signal to noise ratio (PSNR) was 9.1934 dB and had an entropy of 7.999 bits. The correlation coefficient of 0.0001, 0.0019, and 0.0003 for horizontal, vertical and diagonal directions was obtained. The watermark could be satisfactorily recovered from the cover, even with the addition of noise. The extracted watermark had a PSNR above 30 dB, with normalized cross-correlation (NCC) above 0.9, bit error rate (BER) below 0.1 and structural similarity index metric (SSIM) above 0.9. These results make the proposed algorithm suitable for authentication and encryption. [ABSTRACT FROM AUTHOR]

This research proposes a novel high-capacity-based reversible data embedding strategy for e-healthcare applications. The proposed reversible embedding scheme for electronic patient records (EPR) replaced the conventional embedding and interpolation techniques with a simple pixel-to-block-level transformation, repeated pixel differencing (RPD) and conditional pixel permutation (CPP) strategies. A fragile watermark image combined with EPR is employed to identify tamper detection in medical stego-images. In the proposed pixel-to-block conversion, a pixel is replicated to a 2 × 2 pixel block to facilitate the reversibility of EPR data. For embedding, RPD determines and adjusts the 2 × 2 pixel differences based on EPR and watermark data. Further, to ensure high imperceptibility for the human visual system proposed scheme computes the average value of pixels that must similar to the seed pixel. To maintain a histogram invariant stego-images, a permutation of 2 × 2 pixels is employed to embed additional secret data bits while exploiting the CPP strategy. The proposed scheme is extensively evaluated on + 2000 images regarding embedding capacity, perceptual imperceptibility, and tamper detection while employing different image processing attacks. Experimental results show that the proposed scheme achieved an average of 2.24 bpp with 41.27 dB PNSR on medical images and 2.49 bpp with 40.68 PSNR with general images. The proposed strategy outperformed existing approaches in terms of high embedding capacity, acceptable visual imperceptibility, and tamper detection while ensuring the 100% reversibility of EPR data in medical images. [ABSTRACT FROM AUTHOR]

This article utilizes the discrete wavelet transformation to introduce an advanced 3D object watermarking model depending on the characteristics of the object's vertices. The model entails two different phases: integration and extraction. In the integration phase, a novel technique is proposed, which embeds the secret grayscale image three times using both the encrypted pixels and the vertices' coefficients of the original 3D object. In the extraction phase, the secret image is randomly extracted and recaptured using the inverse phase of the integration technique. Four common 3D objects (Stanford bunny, horse, cat figurine, and angel), with different faces and different vertices, are used in this model as a dataset. The performance of the proposed technique is evaluated using different metrics to show its superiority in terms of execution time and imperceptibility. The results demonstrated that the proposed method achieved high imperceptibility and transparency with low distortion. Moreover, the extracted secret grayscale image perfectly matched the original watermark with a structural similarity index of 1 for all testing models. [ABSTRACT FROM AUTHOR]

The secure authentication of user data is crucial in various sectors, including digital banking, medical applications and e-governance, especially for images. Secure communication protects against data tampering and forgery, thereby bolstering the foundation for informed decision-making, whether managing traffic, enhancing public safety, or monitoring environmental conditions. Conventional visual cryptographic protocols offer solutions, particularly for color images, though they grapple with challenges such as high computational demands and reliance on multiple cover images. Additionally, they often require third-party authorization to verify the image integrity. On the other hand, visual cryptography offers a streamlined approach. It divides images into shares, where each pixel represented uniquely, thus allowing visual decryption without complex computations. The optimized multi-tiered authentication protocol (OMTAP), which is integrated with the visual sharing scheme (VSS), takes secure image sharing to the next level. It reduces share count, prioritizes image fidelity and transmission security, and introduces the self-verification of decrypted image integrity through asymmetric key matrix generators, thus eliminating external validation. Rigorous testing has confirmed OMTAP's robustness and broad applicability, thereby ensuring that decrypted images maintain their quality with a peak signal-to-noise ratio (PSNR) of 40 dB and full integrity at the receiver's end.

Abstract Random grids are a method for visual secret sharing, whereby a secret image is encoded into a number of shares, each of which is maximally entropic. There has been growing interest in hiding multiple images in a scheme, such that additional images are revealed by stacking the shares in different ways. This paper proposes a metaheuristic method for generating schemes that allow for a wide range of transformations, or even combinations thereof, to reveal an arbitrary number of secret images. Up to 10 multi-secrets are shown in this paper, as well as hiding multiple secrets in a general access structure. To remove noise from these schemes an algorithm is proposed to extract the information from the noise, and in all cases, relative contrasts are given. In one example, six images are hidden in two shares, such that the mean relative contrast under OR-stacking is 0.152, under XOR-stacking 0.278, and with noise removed, it is 0.74. In an example hiding 10 images in two shares, the values are respectively 0.136, 0.206 and 0.679, respectively.

In today’s era of far-reaching usage of satellite imagery across diverse fields such as remote sensing, environmental monitoring, and national security, the authenticity and integrity of these images have become paramount. However, ensuring the trustworthiness of satellite images remains a challenge, particularly in scenarios where unauthorized access or tampering can lead to severe consequences. This paper proposes a novel solution to address this challenge by means of a self-authenticating multi-tone secret sharing visual cryptography (VC) scheme with meaningful shares. The proposed approach incorporates novel processes, i.e., SPICE (secure pixel integration for covert embedding) and EX-CEP (extraction of covertly embedded pixels) for generation and extraction of secret shares at the sender and receiver side, respectively. Prior to share generation, the satellite image is encrypted and processed to generate a secret hash value which is used for establishing the authenticity and integrity of the received satellite image. The presented work delineates an innovative approach which integrates a comprehensive set of features, i.e., Image Encryption, Self-Authentication, Integrity Verification, Meaningful Shares Construction (from full 8-bit grayscale Meaningless Shares), 100% Original Secret Reconstruction, No Contrast Loss, No Share Expansion, under one umbrella. This approach is distinguished by its holistic one-stop solution strategy, which seamlessly amalgamates multiple novel techniques into a singular, cohesive framework. Exhaustive set of experiments have been performed to demonstrate the efficacy of the proposed approach and to substantiate it’s superiority over the existing state-of-the-art VC approaches. Through comprehensive experimentation, the presented work underscores the effectiveness of the proposed scheme in safeguarding sensitive satellite imagery.

Cloud computing security has emerged as one of the most significant trends in the information technology (IT) sector, and it is currently widely used in that sector, particularly with the growth of information in the cloud. The security of data stored in the cloud, and when it is transferred between users and servers, is very important. secure communication and data transfer can be achieved through the use of steganography and visual cryptography. It is one of the most important technologies for securing data and authenticating it so that only the sender and the receiver can be aware of the hidden information as well as transmitting it. In contrast, visual cryptography is a cryptographic technology that encrypts data. By having these two different branches, it is difficult for an attacker to compromise the data's confidentiality. The purpose of this paper is to review several steganography and visual cryptography that have been proposed to improve cloud security and make it more secure against cyberattacks and eavesdropping. The primary goal of this study is to investigate the capabilities of secured data, which are frequently employed by researchers. Additionally, each secured data domain's advantages and disadvantages are investigated. In order to strengthen the security mechanisms, this research concludes that visual cryptography approaches could be combined with steganography and cloud computing in the secured data realm.

Multimedia data encryption is so crucial because the multimedia encryption algorithm needs more time and memory, and it is difficult to implement. Because of this, the hyperchaotic image encryption technique is becoming more and more popular, which uses little memory, time, or energy and offers the highest level of security for low-powered devices. This study offers a comprehensive overview of modern hyperchaotic systems. By focusing on these complex systems' uniqueness and fundamental features, a study of their dynamic behavior is offered. Such systems are now being used more and more in a variety of industries, including finance, secure communication, and encryption, for example. In reality, every field calls for particular performances of unusual complexity. This research then suggests a specific classification based on the crucial hyperchaotic characteristic, Lyapunov exponent, the equilibrium points, dynamical behavior, NPCR, and UACI..

In today's digital landscape, securing multimedia visual information—specifically color images—is of critical importance across a range of sectors, including the burgeoning fields of logistics and supply chain management. Traditional Visual Cryptography (VC) schemes lay the groundwork for encrypting visual data by fragmenting a secret image into multiple shares, thereby ensuring no single share divulges the secret. Nevertheless, VC faces challenges in ascertaining the integrity of reconstructed images, especially when shares are manipulated maliciously. Existing solutions often necessitate additional shares or a trusted third party for integrity verification, thereby adding complexity and potential security risks. This paper introduces a novel Cheating-Resistant Visual Cryptographic Protocol (CRVC) for Color Images that aims to address these limitations. Utilizing self-computational models, this enhanced protocol simplifies the integrated integrity verification process, eliminating the need for extra shares. A standout feature is its capability to securely transmit meaningful shares for color images without compromising the quality of the reconstructed image as the PSNR maintains to be ∞. Experimental findings substantiate the protocol's resilience against quality degradation and its effectiveness in verifying the authenticity of the reconstructed image. This innovative approach holds promise for a wide array of applications, notably in sectors requiring secure document transmission, such as Logistics and Supply Chain Management, E-Governance, Medical and Military Applications.

In the digital era, data transmission plays a crucial role, encompassing various forms such as text, images, and videos. Industries such as banking, medical, marketing, social media, and business applications heavily rely on images for communication with customers and others. However, this increased reliance on digital communication has attracted Cyber Attackers (CAs), individuals or entities that exploit network weaknesses and disturb data integrity, leading to vulnerabilities in data transmission. The healthcare industry, in particular, has faced significant costs due to data breaches, as indicated by the Cost of a Data Breach Report 2021. Securing such data during communication is a key challenge. Visual Cryptography (VC) emerges as a powerful solution for secure image transfer. VC's share generation module encrypts the image and divides it into multiple shares, which are then communicated to recipients. Individual shares do not disclose classified information. At the destination, the shares are digitally or physically stacked to reconstruct the original image without the need for complex mathematical operations or additional hardware. Key constraints in VC include the security of share images, the quality of the reconstructed image, pixel expansion issues, and computational complexity. Despite the significance of VC, existing research papers often focus on specific types of schemes, leaving gaps in comprehensive comparisons and coverage of the state-of-the-art. To address this, we propose a new Progressive Meaningful Visual Cryptography (PMVC) method in this paper for transferring secret images by triggering an error instance. The proposed method generates meaningful shares and ensures the quality of the reconstructed image, achieving a peak signal-to-noise ratio (PSNR) of up to 37 dB without pixel expansion issues. Additionally, the proposed method works on (n, n) VC schemes and supports grayscale secret images. [ABSTRACT FROM AUTHOR]

In traditional secret image sharing schemes, shareholders have similar situations, and to recover the secret image, they must be present as many as the threshold. However, in scenarios where the shareholders occupy different positions, essential and non‐essential, the use of essential secret image sharing schemes becomes necessary. This article presents a novel verifiable essential secret image sharing scheme based on LWEs that incorporates Bloom filters and hash functions for verification purposes. The proposed scheme for a secret image does not require any pre‐processing. The shadow images of both essential and non‐essential shareholders are of the same size, eliminating the need for concatenating sub‐shadows. Furthermore, shadow images for essential and non‐essential shareholders are produced simultaneously in a single step. The scheme is also quantum safe thanks to the use of quantum‐resistant primitives. The experimental results confirm the security and efficiency of the proposed scheme. [ABSTRACT FROM AUTHOR]

Random grids are a method for visual secret sharing, whereby a secret image is encoded into a number of shares, each of which is maximally entropic. There has been growing interest in hiding multiple images in a scheme, such that additional images are revealed by stacking the shares in different ways. This paper proposes a metaheuristic method for generating schemes that allow for a wide range of transformations, or even combinations thereof, to reveal an arbitrary number of secret images. Up to 10 multi-secrets are shown in this paper, as well as hiding multiple secrets in a general access structure. To remove noise from these schemes an algorithm is proposed to extract the information from the noise, and in all cases, relative contrasts are given. In one example, six images are hidden in two shares, such that the mean relative contrast under OR-stacking is 0.152, under XOR-stacking 0.278, and with noise removed, it is 0.74. In an example hiding 10 images in two shares, the values are respectively 0.136, 0.206 and 0.679, respectively. [ABSTRACT FROM AUTHOR]

Cross-view geo-localization aims to locate street-view images by matching them with a collection of GPS-tagged remote sensing (RS) images. Due to the significant viewpoint and appearance differences between street-view images and RS images, this task is highly challenging. While deep learning-based methods have shown their dominance in the cross-view geo-localization task, existing models have difficulties in extracting comprehensive meaningful features from both domains of images. This limitation results in not establishing accurate and robust dependencies between street-view images and the corresponding RS images. To address the aforementioned issues, this paper proposes a novel and lightweight neural network for cross-view geo-localization. Firstly, in order to capture more diverse information, we propose a module for extracting multi-scale features from images. Secondly, we introduce contrastive learning and design a contrastive loss to further enhance the robustness in extracting and aligning meaningful multi-scale features. Finally, we conduct comprehensive experiments on two open benchmarks. The experimental results have demonstrated the superiority of the proposed method over the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Cell and organelle shape are driven by diverse genetic and environmental factors and thus accurate quantification of cellular morphology is essential to experimental cell biology. Autoencoders are a popular tool for unsupervised biological image analysis because they learn a low-dimensional representation that maps images to feature vectors to generate a semantically meaningful embedding space of morphological variation. The learned feature vectors can also be used for clustering, dimensionality reduction, outlier detection, and supervised learning problems. Shape properties do not change with orientation, and thus we argue that representation learning methods should encode this orientation invariance. We show that conventional autoencoders are sensitive to orientation, which can lead to suboptimal performance on downstream tasks. To address this, we develop O2-variational autoencoder (O2-VAE), an unsupervised method that learns robust, orientation-invariant representations. We use O2-VAE to discover morphology subgroups in segmented cells and mitochondria, detect outlier cells, and rapidly characterise cellular shape and texture in large datasets, including in a newly generated synthetic benchmark. In image analysis, the shape properties of cells/organelles should be unaffected by image orientation. Conventional autoencoder (AE) methods can be sensitive to orientation. Here, the authors develop an unsupervised AE method that learns robust, orientation-invariant representations. [ABSTRACT FROM AUTHOR]

Visual cryptography (VC) is a cryptographic technique that allows the encryption of a secret image into multiple shares. When the shares of a qualified subset are superimposed, the original secret image can be visually recovered. Region incremental visual cryptography (RIVC) is a class of visual cryptography; it encrypts a single image into a shared image with multiple levels of secrecy, and when decrypted, the secret image of each region can be gradually recovered. Traditional VC encrypts two black-and-white images, and its recovery method is equivalent to a logical OR operation. To obtain a better recognizability of the restored image, the XORoperator becomes a simple and efficient method of encryption and decryption. Because the XOR operation needs extra cost or equipment, if the equipment cannot be obtained, the scheme can be more flexible if the secret can still be restored by using OR decryption (superimpose). In this paper, we propose a novel RIVC that allows encoding multiple secret regions of a secret image into n random grids. Both the OR operation and the XOR operation can be used as operations during decryption. The proposed scheme is evaluated by simulation, and the experimental result shows its correctness, effectiveness and practicability. [ABSTRACT FROM AUTHOR]

In Cryptography the covert image share creation method and multiple image encryption and decryption are used with different algorithms. In this work, Visual Cryptography (VC) is used for the outline of shares that have been generated from the novel image. Red, Green, and Blue pixel shares are one by one formed by the Visual Secret Sharing (VSS) Scheme. It proposed the ECC method for image encryption and decryption using Rubik's cube image encryption algorithm. The encryption method is by a public key cryptography generator and the decryption method is done by the secret key arbitrarily generators of the ECC method. For humanizing, the performance analysis of Elliptic Curve Cryptography methods, such as the optimization techniques, was used for PSNR, MSE, and the Number of Pixel Changing Rate (NPCR) and (UACI). The outcome explains that the planned algorithm is improved over various other methods compared to the presented methods. The future technique is implemented with Matlab coding. [ABSTRACT FROM AUTHOR]

With the enhancement of information volume, people are not satisfied with transmitting only a single secret image at a time but chase to hide multiple secret images in a single picture; however, the large-capacity steganographic scale can easily lead to the degradation of the quality of the image, which attracts the attention of eavesdroppers. In this paper, we propose a Chaotic mapping-enHanced imAge Steganography nEtwork (CHASE), which pioneers to hide colour images in grey images and reduces the difference between the container image and the cover image through the image permutation method, so as to enhance the security of the steganography. The method demonstrates excellent steganalysis resistance in experiments and introduces Generative Adversarial Networks (GANs) to improve the image fidelity in large-capacity steganographic scales. The fusion of chaotic mapping and GAN optimisation enables the steganographic network to simultaneously balance security and image quality. The experimental results show that CHASE can keep the secret image with good invisibility under large-capacity steganographic scales, and at the same time, it can reveal the secret image with high fidelity, and its steganalysis-resistant capability is much better than other state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Summary: This study presents a quantum secret sharing (QSS) protocol designed using Grover's search algorithm in a noisy environment. The proposed protocol utilizes Grover's three‐particle quantum state. The proposed scheme is divided into secret information sharing and eavesdropping checking. The dealer prepares an encoded state by encoding the classical information as a marked state and shares the states' qubits between three participants. Using the amplitude‐damping noise and the phase‐damping noise as conventional noisy channels, it can be demonstrated that secret information can be conveyed between participants with some information lost. The security analysis shows the scheme is stringent against malicious participants or eavesdroppers. The simulation analysis is done on the cloud platform IBM‐QE thereby showing the practical feasibility of the scheme. Finally, an application of the proposed scheme is demonstrated in visual cryptography using the GNEQR representation of images. [ABSTRACT FROM AUTHOR]

Visual cryptography is a cryptographic method that encrypts visual facts and the information decrypted appears as an original visual image. Here, the confidential data is shared by dividing the visual details into multiple shares such that the encryption and the decryption are performed for reconstructing the original image back by stacking the splitted shares. However, the data sharing process lacks adequate security protection. To overcome the issues, this paper presents a robust visual cryptography-based data sharing scheme, named Competitive Swarm Improved Invasive Weed Optimization (CSIIWO) for sharing multiple data. Initially, the grayscale input image is shared between several parties, such that the shared image is encrypted and decrypted for retrieving the original image back. However, the cryptographic key generation is done using the devised CSIIWO algorithm such that the cryptographic keys are generated for the data sharing process to maintain confidentiality among multiple parties. Moreover, the devised method achieved the maximum Peak signal-to-noise ratio (PSNR) of 40.749 dB, minimum conditional privacy loss of 0.508, and maximum entropy of 7.987, respectively using Lena image. Furthermore, the proposed scheme can protect the multiple data sharing information and has numerous advantages compared with the previous mechanisms. [ABSTRACT FROM AUTHOR]

In this paper, a blind semi-fragile dual watermarking system for video content authentication and tampering localization is proposed. In this method, two watermarks are tailored for each host video frame. Indeed, the frame index is firstly binary modulated and then, serves as a primary watermark. Subsequently, a second content-based authentication watermark is built up using frame blocks texture features. To improve the security aspect, Torus automorphism mapping is applied under the second watermark before being embedded. The suggested scheme operates in the hybrid domain. In fact, the primary watermark is infused in the host frame following a spatial domain-based embedding technique. However, a frequency domain-based watermarking method, which combines Lifting Wavelet Transform (LWT) and Singular Value Decomposition (SVD), is involved to hide the second watermark. Herein, the most textured blocks are chosen as second watermark holders to enhance the watermarked video perceptual quality. During the detection process, the dissimilarity between the second extracted watermark and its reconstructed version as well as the mismatch between the observed index and the extracted one enable to reveal spatial and temporal tampering, respectively. Experimental results show that the proposed scheme achieves a good visual quality with a large embedding capacity. Furthermore, it can efficiently withstand non-malicious processing while being fragile to frames manipulations and content modification attacks. Moreover, it ensures an accurate tampered areas localization. [ABSTRACT FROM AUTHOR]

Computational creativity modeling, including concept combination, enables us to foster deeper abilities of Artificial Intelligence (AI) agents. Although concept combination has been addressed in a lot of computational creativity studies, findings show incompatibility amongst empirical data of concept combination and the results of the used methods. In addition, even though recent neuroscientific studies show the crucial impact of retrieving concepts' relations explicitly stored in episodic memory, it has been underestimated in modeling creative processes. In this paper, a quantum cognition-based approach is used to consider the context more efiectively and resolve logical inconsistencies. Also, episodic memory is leveraged as the basis for the concept combination modeling process based on the created context. The result of the proposed process is a set of meaningful concepts and expressions as a combination of stimuli and related episodes, which are used to depict a visual collage as an image. The significant improvement in the quality of results in comparison with the existing methods suggests that quantum-like modeling can be considered the foundation for developing AI agents capable of creating artistic images or assisting a person during a creative process. [ABSTRACT FROM AUTHOR]

Recently, three visual cryptography schemes with t-error-correcting capability (VCSs-tEC) were introduced for preventing the shadows carrying additional information from being corrupted by noise interference. However, the concerns on VCS-tEC, such as the average amount of carrying information, decoding of information from shadows, and the demonstration way of a secret, should be considered and improved. In this article, two schemes, namely the (k,n) probabilistic VCS-tEC (PVCS-tEC) and the (2,n) deterministic VCS-tEC (DVCStEC), are proposed. The concept of probabilistic VCS is combined with the Bose-Chaudhuri-Hocquenghem code (BCH code) for designing the (k,n) PVCS-tEC. Furthermore, some constant-weight BCH codewords are adopted to build the (2,n)-DVCS-tEC. Comprehensive results and experiments are demonstrated to clarify the enhancement of information-carrying and decoding by the two proposed methods. [ABSTRACT FROM AUTHOR]

Visual grounding is an essential task in understanding the semantic relationship between the given text description and the target object in an image. Due to the innate complexity of language and the rich semantic context of the image, it is still a challenging problem to infer the underlying relationship and to perform reasoning between the objects in an image and the given expression. Although existing visual grounding methods have achieved promising progress, cross-modal mapping across different domains for the task is still not well handled, especially when the expressions are complex and long. To address the issue, we propose a language-guided residual graph attention network for visual grounding (LRGAT-VG), which enables us to apply deeper graph convolution layers with the assistance of residual connections between them. This allows us to better handle long and complex expressions than other graph-based methods. Furthermore, we perform a Language-guided Data Augmentation (LGDA), which is based on copy-paste operations on pairs of source and target images to increase the diversity of training data while maintaining the relationship between the objects in the image and the expression. With extensive experiments on three visual grounding benchmarks, including RefCOCO, RefCOCO+, and RefCOCOg, LRGAT-VG with LGDA achieves competitive performance with other state-of-the-art graph network-based referring expression approaches and demonstrates its effectiveness. [ABSTRACT FROM AUTHOR]