Secret Image Research Articles

A multi-image compression and encryption scheme based on fractional chaotic map

In this paper, a visual security encryption scheme for multi-color images based on BP neural network and fractional chaotic map is proposed, which disguises secret images as a meaningful visual image. Firstly, three color images are compressed based on BP neural network. Then, according to the pseudo-random sequence generated by fractional chaotic map, the merged compressed images are scrambled by spiral transformation and diffused by XOR, in which the direction and degree of spiral transformation can be adjusted. In order to ensure the visual effect of the camouflage image, the lifting wavelet transform (LWT) is used to decompose the carrier image to obtain the coefficient matrix, and the cipher images are adjusted to a narrow range and embedded into the coefficient matrixes based on the pseudo-random sequence. Finally, visually secure image can be generated by inverse lifting wavelet transform. The reverse algorithm can restore the images by extraction, decryption and decompression. Experimental results verify that the proposed scheme has feasibility, robustness, anti-noise and clipping capability, and the PSNR value is no less than 31.4 under various attacks.

Retraction Note: Secret image sharing scheme with encrypted shadow images using optimal homomorphic encryption technique

Retraction Note: Secret image sharing scheme with encrypted shadow images using optimal homomorphic encryption technique

Image steganography technique based on bald eagle search optimal pixel selection with chaotic encryption

In the digital era, information security becomes a challenging process that can be mitigated by the utilization of cryptography and steganography techniques. Earlier studies on steganography have the risk of exposing confidential data by an anonymous user. For resolving, the limitations related to the existing algorithms, one of the efficient solutions in encryption-based steganography. Encryption techniques act as an important part in protect actual data from illegal access. This study focuses on the design of Bald Eagle Search Optimal Pixel Selection with Chaotic Encryption (BESOPS-CE) based image steganography technique. The presented BESOPS-CE technique effectively hides the secret image in its encrypted version to the cover image. For accomplishing this, the BESOPS-CE technique employs a BES for optimal pixel selection (OPS) procedure. Besides, chaotic encryption was executed for encrypting the secret image, which is then embedded to choose pixel points of the cover image. Finally, embedding and extraction processes are carried out. The inclusion of the encryption process aids in accomplishing an added layer of security. A comprehensive simulation study was used to report on the BESOPS-CE approach's increased performance, and the results are examined from many angles. A thorough comparative analysis revealed that the BESOPS-CE model outperformed more contemporary methods.

Implementation of a steganography system based on hybrid square quaternion moment compression in IoMT

Internet of Medical Things (IoMT) systems generate medical data transmissions between patients, medical experts, and medical centers over public networks, which require high levels of security to protect the content of medical images and the personal information they contain. In this paper, we propose a new stego image encryption scheme based on a new secret image compression method, wavelet transformation, QR decomposition of the cover image, and a new chaotic map. The secret image is compressed by the Hahn-Krawtchouk hybrid quaternion square moments (HK-HQSM), which are optimized by a new hybrid metaheuristic algorithm based on the Salp Swarm Algorithm (SSA) and the Arithmetic Optimization Algorithm (AOA). To increase the security level when transmitting the proposed stego images over public networks, we introduce a new chaotic map based on the 2D fractional Henon map to encrypt the stego image. To demonstrate the effectiveness of the proposed steganography scheme for IoMT, we implemented this scheme on a low-cost Raspberry Pi 4 hardware board. The results of the performed numerical experiments show that our method is secure and provides exceptional robustness against common standard image processing attacks (steganalysis attacks). The results also demonstrate that our strategy is able to work efficiently and quickly when implemented on a Raspberry Pi board.

Reversible data hiding based on histogram and prediction error for sharing secret data

With the advancement of communication technology, a large number of data are constantly transmitted through the internet for various purposes, which are prone to be illegally accessed by third parties. Therefore, securing such data is crucial to protect the transmitted information from falling into the wrong hands. Among data protection schemes, Secret Image Sharing is one of the most popular methods. It protects critical messages or data by embedding them in an image and sharing it with some users. Furthermore, it combines the security concepts in that private data are embedded into a cover image and then secured using the secret-sharing method. Despite its advantages, this method may produce noise, making the resulting stego file much different from its cover. Moreover, the size of private data that can be embedded is limited. This research works on these problems by utilizing prediction-error expansion and histogram-based approaches to embed the data. To recover the cover image, the SS method based on the Chinese remainder theorem is used. The experimental results indicate that this proposed method performs better than similar methods in several cover images and scenarios.

A hybrid approach combining data hiding with visual cryptography for secure extraction of data hiding

Visual cryptography scheme (VCS) naturally provides a solution for protecting a secret image in a group environment. However, most of the existing VCSs proposed so far only protect one secret image. In this work, we design a hybrid scheme combining VCS and data hiding to simultaneously safeguard the secret image and some related information (e.g., the description of the secret image). First of all, a framework for the hybrid scheme is introduced. Algorithms for building the proposed framework are given. Generally, a secret image is partitioned into k shadows in which the additional messages are embedded. By stacking k shadows, the secret image is visually revealed, and meanwhile, the embedded messages can be securely extracted from the stacked result. Moreover, the performance of the proposed technique would suffer as a result when the threshold k becomes larger. At this time, we have larger pixel expansion, smaller contrast, and reduced data hiding efficiency. To make the scheme more practical, an improved approach is presented for reducing the pixel expansion, increasing the visual quality of recovered image, and enhancing the data hiding efficiency. Comprehensive theoretical analysis and experiments are demonstrated to clarify the effectiveness and advantages of the proposed methods.

Efficient reconfigurable architecture to enhance medical image security

Medical images are one of the most critical and sensitive types of data in information systems. For the secure storage and transfer of medical images, confidentiality is the most important aspect. This paper presents efficient embedding technique to enhance medical image security. The Gaussian filters are used as preprocessing to remove high frequency components and then applied to cumulative distribution function (CDF) 5/3 wavelet to obtain LL band features. Similarly, the LL band features of cover image are obtained. The alpha bending technique combines both the LL band features of cover and secret image to form first level of encryption and now with other high frequency bands of LH, HL and HH applied to Inverse CDF 5/3 obtains an encrypted image which is then transferred along with key obtained through other bands of LH, HL and HH. The key generated acts as additional level of security and similarly, at the receiver the opposite operations are performed to obtain the original secrete image. The performance is measured in terms of Peak signal-to-noise ratio (PSNR) and is compared with existing techniques to validate the results. Further, the entire architecture is synthesized on spartan 6 field-programmable gate array (FPGA) board to compare the hardware utilizations.

A Secret JPEG Image Sharing Method Over GF(2 M ) Galois Fields

With the rise of exchanges over the cloud and social networks, JPEG images have taken an important place in world image transmission and storage. In order to avoid security breaches and combat threats on the Internet, numerous JPEG image security methods have been proposed in both the academic and industrial communities. Encryption methods have been specifically designed to make JPEG images visually secure using so called crypto-compression methods. The drawback of crypto-compression is that it depends on only one secret key. Indeed, if this key is lost, so is the totality of the content of the secret original image. In this paper, we propose a secret JPEG image sharing approach. Shamir’s secret sharing scheme over Galois fields is used during the JPEG Huffman coding step, ensuring the visual security of the secret image in the compressed domain, while solving the issue of secret key loss. In addition, we also describe an eco-friendly scenario, dealing with a public shared JPEG image. In this scenario, we can obtain compressed shares because there is no need to duplicate the redundant information. According to our obtained results, our approach is fully format compliant and size preserving when compared to a standard JPEG compression of a secret original image, while ensuring the visual security of the content of the secret original image.

A secret image sharing solution for autonomous vehicles

With the improvement of personal privacy awareness and government agencies' awareness of national security information protection, data access and data security of smart cars is a thorny problem. The fundamental reason is that the key to access and store data is kept in the hands of smart car companies. Although many scholars have made great progress in the research of secret image sharing solutions before, such as progressive visual secret sharing, polynomial based secret image sharing, etc., these encryption schemes are single key encryption and cannot solve the technical problems encountered by the current autonomous vehicle. Therefore, based on the research of previous scholars and taking into account the social problems in solving the existing image sharing, this paper proposes two secret image sharing solutions. One is key sharing solution; The other is Images Sharing solution. Through the theoretical analysis of the application scenario, we can conclude that these two solutions can well solve the problems of whether users, smart car companies or third-party institutions infringe on users' privacy, whether it is due to the security hidden dangers brought by smart car technology, and whether they violate the national information security law.

Camouflaged image cryptosystem based on compressive interference against deep learning

In this paper, our previously proposed compressive interference-based image cryptosystem (CIBC) is utilized to develop a camouflaged image cryptosystem, in which a secret image is camouflaged by a meaningful image. During the encryption process, a secret image is encoded into two sparse and complementary phase only masks (POMs) by CIBC under the constraints of two binary amplitude masks(BAMs), in which the BAM can be taken as a private key. Then, a camouflaged image is encoded into another two POMs by CIBC under the constraints of the two POMs generated in the aforementioned step, and the two final POMs are stored and transmitted as ciphertexts. In the decryption process, only authorized users, who can access the ciphertexts, public and private keys simultaneously, can retrieve the decrypted secret image. Otherwise, even if the eavesdropper cracks the ciphertexts and the public keys, only the camouflaged image can be directly obtained, which can confuse the eavesdropper and then protect the secret image. Several simulation experiments were demonstrated to verify the feasibility and security of this cryptosystem.

Adversarial Attack for Deep Steganography Based on Surrogate Training and Knowledge Diffusion

Deep steganography (DS), using neural networks to hide one image in another, has performed well in terms of invisibility, embedding capacity, etc. Current steganalysis methods for DS can only detect or remove secret images hidden in natural images and cannot analyze or modify secret content. Our technique is the first approach to not only effectively prevent covert communications using DS, but also analyze and modify the content of covert communications. We proposed a novel adversarial attack method for DS considering both white-box and black-box scenarios. For the white-box attack, several novel loss functions were applied to construct a gradient- and optimizer-based adversarial attack that could delete and modify secret images. As a more realistic case, a black-box method was proposed based on surrogate training and a knowledge distillation technique. All methods were tested on the Tiny ImageNet and MS COCO datasets. The experimental results showed that the proposed attack method could completely remove or even modify the secret image in the container image while maintaining the latter’s high quality. More importantly, the proposed adversarial attack method can also be regarded as a new DS approach.

A Novel Fractional Sine Chaotic Map and Its Application to Image Encryption and Watermarking

This article addresses the telecommunications industry’s priority of ensuring information security during the transition to next-generation networks. It proposes an image encryption system that combines watermarking techniques and a discrete fractional sine chaotic map. The authors also incorporate the principles of blockchain to enhance the security of transmitted and received image data. The proposed system utilizes a newly developed sine chaotic map with a fractional difference operator, exhibiting long-term chaotic dynamics. The complexity of this map is demonstrated by comparing it with three other fractional chaotic maps from existing literature, using bifurcation diagrams and the largest Lyapunov exponent. The authors also show the map’s sensitivity to changes in initial conditions through time-series diagrams. To encrypt images, the authors suggest a method involving watermarking of two secret images and encryption based on blockchain technology. The cover image is watermarked with the two hidden images using discrete wavelet transformations. Then, the image pixels undergo diffusion using a chaotic matrix generated from the discrete fractional sine chaotic map. This encryption process aims to protect the image data and make it resistant to unauthorized access. To evaluate the algorithm, the authors perform statistical analysis and critical sensitivity analysis to examine its characteristics. They also analyse different attacks to assess the algorithm’s ability to resist such threats and maintain image quality after decryption. The results demonstrate that the proposed algorithm effectively defends against attacks and ensures image security.

Visually meaningful image encryption combining with reversible data hiding in encrypted images

At present, most image encryption schemes directly change plaintext images into ciphertext images without visual significance, such ciphertext images can be detected and therefore subject to various attacks. To protect the content security and visual safety of images, a visually meaningful image encryption (VMIE) algorithm combining with Reversible Data Hiding in Encrypted Images (RDHEI) is proposed. First, the secret image is encrypted and additional information is embedded by Chen hyperchaotic system and prediction error expansion (PEE) method. Then the source image is encrypted by a Lorentz hyperchaotic system. Finally, bit-xor operation is performed on the resulting encrypted image and the result is saved in a cloud database to generate an indexing key using SHA-256,which enables the receiver to recover the secret image with the resource image and the key alone. The scheme combines with the RDHEI, improving the transmission efficiency and has no image quality problems.The experimental results and security analysis show that the image encryption scheme has sufficient key space, strong key sensitivity and wide applicability.

Natural share-based lightweight (n, n) single secret image sharing scheme using LSB stuffing for medical images

Natural share-based lightweight (n, n) single secret image sharing scheme using LSB stuffing for medical images

Privacy Protection of Digital Images Using Watermarking and QR Code-based Visual Cryptography

The increase in information sharing in terms of digital images imposes threats to privacy and personal identity. Digital images can be stolen while in transfer and any kind of alteration can be done very easily. Thus, privacy protection of digital images from attackers becomes very important. Encryption, steganography, watermarking, and visual cryptography techniques to protect digital images have been proposed from time to time. The present paper is focused on the enhancement of privacy protection of digital images utilizing watermarking and a QR code-based expansion-free and meaningful visual cryptography approach which generates visually appealing QR codes for transmitting meaningful shares. The original secret image is processed with a watermark image (copyright logo, signature, and so on), and then halftoning of the watermarked image has been done to limit pixel expansion. Then, the halftoned image has been partitioned using VC into two shares. These shares are embedded with a QR code to make the shares meaningful. Lossless compression has been performed on the QR code-based shares. The compression method employed in visual cryptography would save space and time. The proposed approach keeps the beauty of visual cryptography, i.e., computation-free decryption, and the size of the recovered image the same as the original secret image. The experimental results confirm the effectiveness of the proposed approach.

VSBSIS: A verifiable SVD-based secret image sharing scheme for lossless and efficient reconstruction

Secret image sharing is a useful technique in various domains of image processing, like data hiding, image security, and visual authentication. It maintains the secrecy of an image by distributing it among many participants, known as shares. This article introduces a (n,n) singular value decomposition-based grayscale and color image-sharing techniques with verifiable and lossless reconstruction. A verifiable secret image sharing determines whether the reconstructed image is the original secret. The addition of all n shares is sufficient to reveal the secret image with no loss of information. Encryption before sharing and decryption after the addition of shares have been applied to resist information leakage of the reconstructed image by adding less than n shares. The verifiability, correctness, performance evaluation, and experimental security analysis of the proposed VSBSIS scheme have established its efficiency. Comparison with other contemporary polynomial-based secret image-sharing schemes demonstrates the efficient reconstruction of the proposed scheme.

Lossless Reversible Data Hiding in Encrypted Image for Multiple Data Hiders Based on Pixel Value Order and Secret Sharing

Reversible data hiding in encrypted images (RDH-EI) is instrumental in image privacy protection and data embedding. However, conventional RDH-EI models, involving image providers, data hiders, and receivers, limit the number of data hiders to one, which restricts its applicability in scenarios requiring multiple data embedders. Therefore, the need for an RDH-EI accommodating multiple data hiders, especially for copyright protection, has become crucial. Addressing this, we introduce the application of Pixel Value Order (PVO) technology to encrypted reversible data hiding, combined with the secret image sharing (SIS) scheme. This creates a novel scheme, PVO, Chaotic System, Secret Sharing-based Reversible Data Hiding in Encrypted Image (PCSRDH-EI), which satisfies the (k,n) threshold property. An image is partitioned into N shadow images, and reconstruction is feasible when at least k shadow images are available. This method enables separate data extraction and image decryption. Our scheme combines stream encryption, based on chaotic systems, with secret sharing, underpinned by the Chinese remainder theorem (CRT), ensuring secure secret sharing. Empirical tests show that PCSRDH-EI can reach a maximum embedding rate of 5.706 bpp, outperforming the state-of-the-art and demonstrating superior encryption effects.

Formula omitted] Regional Secret Image Sharing over Finite Fields

Secret image sharing (SIS), a tool capable of distributing a private image among certain number of shareholders, ensures both authorized recovery and unauthorized forbidding of the same. However, usually, in SIS every pixel is treated with equal weight. This is a hindrance in case of partial query to the original secret image, where usual SIS might over-inform the querier. To prevent this over-spilling of information, we introduce, in this work, the notion of Regional Secret Sharing, where access to a special region is not possible in general, unless an essential participant submits his shadow. We formally define (t,k,n)-Regional secret image sharing ((t,k,n)-RSIS) and provide a construction for the same using polynomial based secret image sharing. Our construction which is done over a finite field is completely lossless. We also formally prove the protocol’s behaviour in different cases of authorized access and unauthorized access. Moreover, we support our constructions with sufficient experimental results. This is the first usage of the notion of region in secret image sharing. Our construction is information theoretically secure, meaning we do not assume any computational assumptions for the adversary, in the semi-honest model and it does not require any preprocessing unlike most SIS schemes, making the scheme efficient as well.

Reversible image-hiding algorithm based on singular value sampling and compressive sensing

A reversible image-hiding algorithm based on a novel chaotic system is proposed using compressive sensing (CS) and singular value sampling (SVS) techniques. In the first stage, a novel mathematical model is constructed to extract the plain messages from the secret plain image, and the public-key Rivest–Shamir–Adleman (RSA) algorithm is adopted to encrypt these messages, obtaining the corresponding cipher messages. Then, another mathematical model of key transformation is constructed to transform above messages into the initial keys, which is used to produce a random key stream. In the second stage, the secret plain image is scrambled by a pre-encryption operation, and the corresponding singular values are obtained by singular value decomposition (SVD). Then, these values are partitioned, and zero blocks are identified and removed. Thereafter, the singular values of the blocks with non-zero elements are sampled by CS, with filled by zero elements again. In the third stage, high energy coefficients are removed and replaced by zero elements to obtain new sampling values. Then, the carrier image is processed by discrete wavelet transform (DWT). Next, new sampling values are embedded into the wavelet coefficients, and the inverse DWT is performed. Thus, a new carrier image containing the secrets is obtained. The advantages are: (1) A new chaotic system ImpTDCS is proposed to have a better behavior. (2) A novel model EMM is built to extract plain messages from secret image. (3) Multi-images can be embedded, which can hide more secret information each time. (4) SVD is operated followed by SVS on non-zero blocks, reducing transmission bandwidth. (5) High energy coefficients of SVS are removed before embedding operation, guaranteeing effectively the visual quality of carrier image containing secrets.

A secure and effective image encryption scheme by combining parallel compressed sensing with secret sharing scheme

In the complex network environment, it is becoming more and more significant to protect the security of information during transmission. A secure and effective image encryption scheme by combining parallel compressed sensing with secret sharing scheme is presented in this paper. Firstly, an image is measured by parallel compressed sensing, which not only realizes compression and encryption in the meantime, but also reduces computational complexity and storage space, and enhances transmission efficiency. Secondly, a block Arnold transformation is applied to process the measurement value image, and the obtained image is called a secret image, so as to achieve the effects of scrambling and encryption. Then, the secret image is partitioned into n shadow images by Shamir’s (t,n)-threshold secret sharing scheme, at least any t of n shadows images are able to recover the secret image, so the size of shadow images can be adjusted according to different application scenarios, which is flexible. This method realizes the encryption effect, and enhances the security of the secret image. Finally, to ensure the security of shadow images, the Zigzag confusion is introduced to process n shadow images and realizes the encryption effect. Experimental results manifest that our scheme realizes security and availability of the network system under the condition of limited resources.