To enhance shares visual quality and security, meaningful secret image sharing relies on pre-input cover images to endow shadow images with interpretable semantics. However, the recently proposed schemes often yield shadows with mediocre visual quality and compromised security, such as vulnerability to statistical analysis or information leakage. Generative SIS (GSIS) introduces image generation or other operations, either to generate high-quality shadows or to eliminate the need for pre-input covers. Our prior \((2,2)\) -GSIS generated meaningful shares without covers but incurred non-critical leakage and did not support lossless reconstruction. Grayscale image colorization, being a widely adopted image processing operation, offers a promising route for GSIS by enriching semantics through chrominance synthesis. We introduce a colorization-driven GSIS. Chrominance components are shared via a \((k,n)\) -threshold SIS. Near-neutral chrominance from color templates provides structural priors that guide the synthesis of share pixels. The generated chrominance supersedes the template values and directly participates in colorization. This dynamic constraint departs from the linear modification paradigm of cover-based schemes, yielding shares that are visually natural and semantically preserved, without information leakage, and enabling lossless recovery from any \( k \) of \( n \) shares. Theoretical analysis and experiments validate the effectiveness and advantages of the framework.

Deep learning models face the threat of adversarial attacks, which challenges their application. Moving Target Defense (MTD) is a defense paradigm that thwarts attacks by constantly changing the targets’ features and restricting the predictability of targets. Recent works have applied MTD in adversarial defense but rely on maintaining a model set and assuming a weak adversary, which causes extra storage and unreliable evaluation of the robustness of the methods. This paper proposes the MTD-Net that realizes MTD in a single neural network. In the training stage, MTD-Net parameters are randomly disabled to ensure desirable accuracy on diversified parameter groups. During each query, MTD-Net dynamically chooses several groups of parameters and aggregates their inference results for final prediction. The parameters MTD-Net chooses for inference are unpredictable, even for adversaries possessing the model’s weights. Thus, MTD-Net achieves factual unpredictability under strong whitebox attacks. We evaluate MTD-Net on two widely used datasets, i.e., GTSRB and CIFAR10. The experimental results demonstrate that MTD-Net achieves superior performance compared to existing MTD defense under adversarial attacks and is applicable to multiple architectures.

The security of deep learning (DL) libraries is crucial due to their central role in developing AI applications. Fuzzing has become a key technique for discovering bugs in DL libraries, but generating high-quality seeds still poses a significant challenge. Although large language models (LLMs) offer promising opportunities, current methods that utilize single-agent frameworks for seed generation often produce invalid seeds. This issue arises from the complexities of DL API structures and the inherent randomness of LLMs, which ultimately reduce fuzzing efficiency. To overcome these challenges, we propose a collaborative multi-agent framework that utilizes specialized LLM-driven agents for iterative seed refinement. This framework consists of three components: (1) a coding agent that incorporates historical bug knowledge to produce the initial bug-prone seeds,(2) a repair agent performs static analysis on the initial seeds and repairs the invalid seeds, and (3) a mutation agent leverages four mutation operators to explore the test space thoroughly.Our framework improves seed validity and functional diversity through ongoing collaboration among agents and established feedback loops. Experimental evaluations show that our approach achieves a 20% increase in seed validity compared to state-of-the-art methods and uncovers 12 previously unknown bugs in popular DL libraries.

Recent years have seen the rapid development of smartphone cameras, enabling high-quality capture of on-screen content and facilitating widespread unauthorized duplication of digital content. While screen-captured images are ubiquitous in daily sharing and commercial activities, the lack of robust copyright protection mechanisms for this specific scenario remains a critical challenge. The copyrights of image creators cannot be effectively safeguarded. Traditional robust watermarking approaches, which primarily focus on digital noise, often fail to resist the unique distortions during the screen-shooting process, such as luminance distortion, perspective distortion, and moiré distortion. To address this challenge, we propose a flow-based screen-shooting robust watermarking framework, whose architecture is comprised of a flow-based watermark network and an invertible denoising network. Additionally, we constructed a screen-shooting noise image dataset and constructed an invertible noise simulation network to model the screen-shooting noise. The network achieves invertible noise modeling through a bidirectional process. The forward process simulates the noise, and the backward process removes the noise. Experimental results demonstrate that, compared to existing robust watermarking methods, our method achieves superior robustness against screen-shooting noise. The invertible noise simulation network exhibits excellent denoising capabilities, and the average PSNR of the watermarked images is up to 39 dB, the watermark information extraction accuracy is up to 98%, ensuring both high imperceptibility and robustness.

Adversarial attacks can cause abnormal behavior in deep neural networks by adding imperceptible perturbations to input data. Adversarial purification is an effective defense method by transforming adversarial data into clean data. Existing purification methods utilize only simple corruptions and specified reconstructors to eliminate perturbations, and thus are non-adaptive to different attack algorithms. To address this challenge, we propose an adaptive adversarial purification framework, which combines multiple Destruction and Reconstruction (D&R) operations to form a multi-stage D&R chain. The Destruction operations consist of corruptions in both spatial and frequency domains. The Reconstruction operations are implemented by deep networks trained respectively for corresponding corruptions to restore images. The D&R chain is constructed dynamically during purification based on the link probabilities of D&R operations with a self-supervised search algorithm. We test our framework on CIFAR10 datasets under five attacks. The experiment results indicate that the proposed framework can adapt to a wide range of attacks and achieve comparable performance.

The Asmuth and Bloom threshold secret sharing (AB-SS) is a classical introduction of the Chinese remainder theorem (CRT) to secret sharing, offering low computational complexity compared to other branches of secret sharing. For decades, numerous schemes have been proposed for practical applications of AB-SS, such as secret image sharing (SIS). However, in terms of security, AB-SS has proved to be neither ideal nor perfect, and its derivatives in image sharing exhibit vulnerabilities associated with secret leakage. This paper studies the security issues in the SIS schemes derived from AB-SS and improves the core sharing principle of AB-SS to enhance security in image protection. First, for$(2,n)$-CRTSIS schemes, we exploit the vulnerability in a single share image to crack the confidential information of the original image, including secret pixel values and the ratio of different pixels. Then, by employing the XOR operation, we introduce a chain obfuscation technology and propose a secure image sharing scheme based on the Chinese remainder theorem (COxor-CRTSIS). The COxor-CRTSIS scheme utilizes integer linear programming for achieving lossless recovery without segmentation and eliminates potential secret disclosure risks without additional encryption. Furthermore, to comprehensively evaluate the security of existing schemes, this paper presents three metrics, information loss rate, fluctuation degree, and coverage rate, enabling a quantitative comparison of security for the first time. Theoretical analyses and experiments are conducted to validate the effectiveness of our scheme.

$(k,n)$Threshold secret image sharing (SIS) hides a secret image within$n$shadows, and at least$k$shadows are needed for recovery. Due to the popularity and frequency of JPEG recompression, there is a need for robust secret image sharing (ROSIS) designed for JPEG images that is resilient to recompression for practical SIS applications. The current state-of-the-art ROSIS, which relies on error-correcting codes (ECC), is effective only for JPEG compression with quality factors (QFs) of 99 and 100. However, it generates noise-like shadow images that are confined to the spatial domain. In this paper, we present SBC-ROSIS (Robust Secret Image Sharing Scheme Resistant to JPEG Recompression Based on Stable Block Condition), a novel ROSIS scheme that utilizes a stable block condition to guarantee the invariance of discrete cosine transform (DCT) coefficients during JPEG recompression, significantly enhancing the robustness of the scheme. By employing a polynomial-based secret sharing (SS) algorithm, we construct DCT blocks that adhere to stable block condition either directly or through strategic global regulation. Additionally, we carefully consider the similarity between the generated DCT blocks and the original cover DCT blocks. Furthermore, we devised a tailored evaluation methodology specifically for ROSIS. Extensive experimental results indicate that SBC-ROSIS can effectively process JPEG images, achieving a balance among security, robustness, concealment, and adherence to the$(k, n)$threshold, without relying on steganography, ECC, or pixel expansion, and demonstrating robust performance in realistic recompression scenarios.

In recent years, secret image sharing (SIS) has attracted extensive attention in the academic community due to its advantages of loss tolerance and low computational complexity. To enhance the robustness of SIS system, it is vital to study SIS technology that can resist shadow image cropping. Unfortunately, the current research on this topic is limited. In view of this, this paper proposes a robust SIS scheme for color images, which can resist large-scale shadow image cropping. The proposed scheme generates shadow images of the same size as the original secret image by integrating SIS, error correction coding, and pixel re-arrangement techniques. Even in the extreme case that all shadow images are cropped by 25%, it can still achieve lossless recovery regardless of whether the cropping positions of each shadow image intersect or overlap. In addition, it can resist shadow image noise, such as salt-and-pepper noise. Experimental results demonstrate that the proposed scheme has significant advantages over existing schemes in robustness and overall performance and is expected to promote the practical application of SIS.

Image secret sharing (ISS) is gaining popularity due to the importance of digital images and its wide application to cloud-based distributed storage and multiparty secure computing. Shadow image authentication generally includes shadow image detection and identification, and plays an important role in ISS. However, traditional dealer-participatory methods, which suffer from significant pixel expansion or storing auxiliary information, authenticate the shadow image mainly during the decoding phase, also known as unidirectional authentication. The authentication of the shadow image in the distributing (encoding) phase is also important for the participant. In this study, we introduce a public key based bidirectional shadow image authentication method in ISS without pixel expansion for a ( k,n ) threshold. When the dealer distributes each shadow image to a corresponding participant, the participant can authenticate the received shadow image with his/her private key. In the decoding phase, the dealer can authenticate each received shadow image with a secret key; in addition, the dealer can losslessly decode the secret image with any k or more shadow images. The proposed method is validated using theoretical analyses, illustrations, and comparisons.

Secret image sharing (SIS) has received increased attention from the research community because of its usefulness in multiparty secure computing, access control, blockchain distributive storage and other security-oriented applications. Prevention of fake and dishonest participants is a key issue that has spurred interest in practical applications of SIS. Unfortunately, most previous SIS schemes failed to detect and locate fake or dishonest participants. In this article, an SIS for a ( k,n )-threshold without pixel expansion is presented, which can detect and locate both fake and dishonest participants. Using a screening operation, the proposed approach fuses the benefits of polynomial-based SIS, visual cryptographic scheme (VCS) , and hash functions to authenticate separate participants both with and without a dealer. In addition, the proposed approach achieves lossless rebuilding of the secret image. Analyses and experiments are conducted in this study to establish the effectiveness of the presented approach.

Abstract Secret image sharing (SIS) is an important method to protect the security of secret images. When part of the shadows generated by the secret sharing is leaked or when the secret image is restored, the shadows and the secret need to be renewed. Aiming at secret image and shadow image renewal, a scheme for renewing secret image and shadow images is proposed. The scheme is to multiply the original and renewed shadow of the corresponding serial number to get a new shadow over finite fields. Our scheme can realise the renewal of the secret image and shadows and has characteristics of the variable threshold, secure public transmission, variable size, and lossless recovery. This paper theoretically analyses and proves the security of the proposed scheme and verifies the effectiveness through a large number of experiments.

With the widespread use of WeChat Mini Programs, their security has attracted more and more attention. The WeChat Mini Program can be accessed by scanning a WeChat Mini Program code. We should protect the code thus to protect the Mini Program. In this paper, based on studying the function in each pattern of WeChat Mini Program codes, a visual secret sharing (VSS) scheme for WeChat Mini Program codes (MPCVSS) with (n,n)(n≥4) threshold is proposed to control and identify the users of Mini Program. MPCVSS combines the error-correcting characteristic of WeChat Mini Program codes with the theory of VSS. A secret WeChat Mini Program code is shared into n shared codes slightly modified from n cover codes. Each shared code is a valid code that can be scanned and decoded correctly. The secret code can be recovered by XORing n shares. The recovered code can be decoded as the same secret Mini Program. Theoretical analysis and experiments show that the proposed VSS scheme is practical and feasible.

Secret image sharing (SIS) can divide a secret image into several shadow images for protection. Information hiding in the sharing domain (IHSD) fuses SIS and information hiding (IH) to simultaneously share any secret image and hide any information, and this technique can be applied in cloud computing, law enforcement and medical diagnoses. IHSD not only marks shadow images with information to prevent malicious tampering and for convenient management, search and identification but also enhances the robustness of IH. In this paper, we first introduce a formal definition of IHSD. Then, we describe a general IHSD model and algorithms with a concrete example in detail. In IHSD, we design the random element utilization model to control the random pixels generated from SIS. Then, we obtain shadow images with hidden information to realize SIS and IH simultaneously. The inputs of SIS with secret images, steganography and extra information in algorithms are without any limitations. Theoretical analyses, experiments and comparisons are presented to prove the effectiveness and feasibility of IHSD. • IHSD is short for information hiding in the sharing domain. • IHSD fuses secret image sharing and information hiding for simultaneous realization. • IHSD is realized by the random element utilization model to control randomness. • IHSD is a general idea applicable to any secret image and any information.

Multiparties in image secret sharing (ISS) need to verify (detect and recognize) each other, which is seldom considered and realized in traditional methods. In this paper, we introduce the definition of multiparty verification. It includes two stages, i.e., a detection stage and a recognition stage, with evaluation methods that are also discussed. A multiparty verification scheme without pixel expansion is developed, which is suitable for both dealer attendance and nonattendance. The classic hash function, public key cryptography and visual cryptography are technically fused in the developed scheme. In the shadow distribution phase, each participant can verify the received shadow using his private key. In the restoration phase, for the case of dealer attendance, he can verify each shadow received using his secret key; for the case of dealer nonattendance, participants can verify each other before exchanging their shadows. We conduct analyses and illustrations to validate the developed scheme.

A mini program code (also known as sunflower code) comes with WeChat mini program APPs. With the popularization of mini program APPs, mini program codes have become more and more widely used. As a new carrier, the study of information hiding technology based on mini program code is of great significance for the expansion of covert communication carriers and can also deal with security problems in advance. At present, to the best of our knowledge, there is no steganographic research based on mini program codes. In this paper, we propose a scheme to embed secret information into mini program codes for the first time. After studying the construction of mini program codes, a coordinate system is constructed to represent its module coordinates. Then, a binary stream of the secret message is embedded into the encoding region or the edge patch. Experiments show that the proposed data hiding scheme is effective and feasible. The embedded secret message could be extracted while keeping the readability of the mini program code. Moreover, the secret payloads of the encoding region and the edge patch for the V-36 mini program code are 72 bits and 29 bits, respectively.

In some particular scenes, the shadows need to be given different weights to represent the participants’ status or importance. And during the reconstruction, participants with different weights obtain various quality reconstructed images. However, the existing schemes based on visual secret sharing (VSS) and the Chinese remainder theorem (CRT) have some disadvantages. In this paper, we propose a weighted polynomial-based SIS scheme in the field of GF (257). We use k , k threshold polynomial-based secret image sharing (SIS) to generate k shares and assign them corresponding weights. Then, the remaining n − k shares are randomly filled with invalid value 0 or 255. When the threshold is satisfied, the number and weight of share can affect the reconstructed image’s quality. Our proposed scheme has the property of lossless recovery. And the average light transmission of shares in our scheme is identical. Experiments and theoretical analysis show that the proposed scheme is practical and feasible. Besides, the quality of the reconstructed image is consistent with the theoretical derivation.

In some particular situations, participants need to recover different secrets both within a group (i.e., intragroup) and between two groups (i.e., intergroup). However, most of the existing multilevel secret sharing (MLSS) and multigroup secret sharing (MGSS) schemes mainly focus on how to protect a secret between one or more groups. In this paper, we propose a polynomial-based scheme to share multiple secret images both within a group and between groups. The random elements’ utilization model of integer linear programming is used to find polynomial coefficients that meet certain conditions so that each participant holds only one shadow image and some of them can recover secrets of both intergroup and intragroup. In addition, our scheme based on polynomials has the advantage of low computational complexity. Theoretical analysis and experiments show that the proposed scheme is feasible and effective.

Because of the importance of digital images and their extensive application to digital watermarking, block chain, access control, identity authentication, distributive storage in the cloud and so on, image secret sharing (ISS) is attracting ever-increasing attention. Share authentication is an important issue in its practical application. However, most ISS schemes with share authentication ability require a dealer to participate in the authentication (namely, dealer participatory authentication). In this paper, we design an ISS for a$(k,n)$-threshold with separate share authentication abilities of both dealer participatory authentication and dealer nonparticipatory authentication. The advantages of polynomial-based ISS and visual secret sharing (VSS) are skillfully fused to achieve these two authentication abilities without sending a share by using a screening operation. In addition, the designed scheme has the characteristics of low decryption (authentication) complexity, lossless decryption and no pixel expansion. Experiments and theoretical analyses are performed to show the effectiveness of the designed scheme.

A secret image is split into shares in the generation phase of secret image sharing (SIS) for a threshold. In the recovery phase, the secret image is recovered when any or more shares are collected, and each collected share is generally assumed to be lossless in conventional SIS during storage and transmission. However, noise will arise during real-world storage and transmission; thus, shares will experience data loss, which will also lead to data loss in the secret image being recovered. Secret image recovery in the case of lossy shares is an important issue that must be addressed in practice, which is the overall subject of this article. An SIS scheme that can recover the secret image from lossy shares is proposed in this article. First, robust SIS and its definition are introduced. Next, a robust SIS scheme for a threshold without pixel expansion is proposed based on the Chinese remainder theorem (CRT) and error-correcting codes (ECC). By screening the random numbers, the share generation phase of the proposed robust SIS is designed to implement the error correction capability without increasing the share size. Particularly in the case of collecting noisy shares, our recovery method is to some degree robust to some noise types, such as least significant bit (LSB) noise, JPEG compression, and salt-and-pepper noise. A theoretical proof is presented, and experimental results are examined to evaluate the effectiveness of our proposed method.

The ‐threshold image secret sharing (ISS) encodes a secret image into n shares. When k or more shares are obtained, the secret image can be decoded; however, less than k shares could decode none of the secret image. ISS primarily includes polynomial‐based ISS and visual secret sharing (VSS). In this study, the authors find that the random elements in ISS can be used not only to hide information but also to obtain more features such as multiple decryptions and comprehensible share. They have established an application model of random elements that is suitable for both polynomial‐based ISS and VSS. On the basis of the model, they have extended three algorithms to achieve information hiding, multiple decryptions and comprehensible share. Experiments indicate the effectiveness of these algorithms.

Abstract Quick response (QR) codes are becoming increasingly popular in various areas of life due to the advantages of the error correction capacity, the ability to be scanned quickly and the capacity to contain meaningful content. The distribution of dark and light modules of a QR code looks random, but the content of a code can be decoded by a standard QR reader. Thus, a QR code is often used in combination with visual secret sharing (VSS) to generate meaningful shadows. There may be some losses in the process of distribution and preservation of the shadows. To recover secret images with high quality, it is necessary to consider the scheme’s robustness. However, few studies examine robustness of VSS combined with QR codes. In this paper, we propose a robust (k, n)-threshold XOR-ed VSS (XVSS) scheme based on a QR code with the error correction ability. Compared with OR-ed VSS (OVSS), XVSS can recover the secret image losslessly, and the amount of computation needed is low. Since the standard QR encoder does not check if the padding codewords are correct during the encoding phase, we replace padding codewords by initial shadows shared from the secret image using XVSS to generate QR code shadows. As a result, the shadows can be decoded normally, and their error correction abilities are preserved. Once all the shadows have been collected, the secret image can be recovered losslessly. More importantly, if some conventional image attacks, including rotation, JPEG compression, Gaussian noise, salt-and-pepper noise, cropping, resizing, and even the addition of camera and screen noises are performed on the shadows, the secret image can still be recovered. The experimental results and comparisons demonstrate the effectiveness of our scheme.

Shadow images generated from Shamir’s polynomial-based secret image sharing (SSIS) may leak the original secret image information, which causes a significant risk. The occurrence of this risk is closely related to the basis of secret image sharing, Shamir’s polynomial. Shamir’s polynomial plays an essential role in secret sharing, but there are relatively few studies on the power and order number of Shamir’s polynomial. In order to improve the security and effectiveness of SSIS, this paper mainly studies the utility of two parameters in Shamir’s polynomial, order number and power. Through the research of this kind of utility, the choice of order number and power can be given under different security requirements. In this process, an effective shadow image evaluation algorithm is proposed, which can measure the security of shadow images generated by SSIS. The user can understand the influence rule of the order number and power in SSIS, so that the user can choose the appropriate order number and power according to different security needs.

In reversible image secret sharing (RISS), the cover image can be recovered to some degree, and a share can be comprehensible rather than noise-like. Reversible cover images play an important role in law enforcement and medical diagnosis. The comprehensible share can not only reduce the suspicion of attackers but also improve the management efficiency of shares. In this paper, we first provide a formal definition of RISS. Then, we propose an RISS algorithm for a (k, n)-threshold based on the principle of the Chinese remainder theorem-based ISS (CRTISS). In the proposed RISS, the secret image is losslessly decoded by a modular operation, and the original cover image is recovered by a binarization operation, both of which are just simple operations. Theoretical analyses and experiments are provided to validate the proposed definition and algorithm.

Different color patterns of quick response (QR) codes, such as RGB, grayscale, and binary QR codes, are widely used in applications. In this paper, we propose a novel XOR-based visual secret sharing (VSS) scheme using grayscale QR codes as cover images and binary QR code as secret image. First, all the codewords of the secret QR code image are encoded into n temporary binary QR code images, which are substituted for the second significant bit planes of the grayscale QR code cover images to generate n shares. Each share is a grayscale QR code image, which can be decoded by a standard QR code decoder, so that it may not attract the attention of potential attackers when distributed in the public channel. The secret image can be recovered by XORing the codewords regions of QR codes which are extracted from the second significant bit planes of the grayscale shares. More importantly, the proposed scheme is robust to JPEG compression, addition of different noises, rotation, resizing, and cropping, which is useful in practice. The effectiveness and robustness of our scheme are shown by the experimental results. The application of QR code is suitable for wireless multimedia data security.

Secret image sharing is a mechanism to protect a secret image among a group of participants by encrypting the secret into shares and decrypting the secret with sufficient shares. Conventional secret sharing schemes have limitations of lossy recovery and pixel expansion for binary images, or complex computation and "All-or-Nothing" for greyscale images. In this paper, a novel progressive secret image sharing(PSS) scheme with threshold and lossless recovery is proposed to overcome these problems. Meanwhile, its meaningful shadows with the same size as secret are beneficial to identify and decrease the suspicion, and it can be directly applied to share grayscale images. Simulations show the advantages and effectiveness of the proposed scheme.

In this paper, a novel visual secret sharing (VSS) scheme with using QR codes is investigated. The proposed visual secret sharing scheme based on QR codes(VSSQR) can visually reveal secret image by stacking k or more shares (shadow images) from all the n QR codes as well as scan the QR code by a QR code reader. Our VSSQR exploits the error correction mechanism in the QR code structure, to embed the bits corresponding to shares generated by VSS from a secret bit into the same locations of QR codes in the processing of encoding QR. Each output share is a valid QR code, which may reduce the likelihood of attracting the attention of potential attackers, that can be scanned and decoded utilizing a QR code reader. The secret image can be recovered by stacking for case (k, n) based on the human visual system without any computation. In addition, it can assist alignment for VSS recovery. The experiment results show the effectiveness of our scheme.