Bi-directional Block Encoding for Reversible Data Hiding over Encrypted Images

With the extensive use of cloud services in different applications, it's a problem for the cloud service provider to manage or process the privacy data that are encrypted by the content owner. Therefore, signal processing technology in the encrypted domain has attracted the attention of researchers. In this paper, we propose a new reversible data hiding method for encrypted images based on two-phase histogram shifting. In the proposed method, the original image is encrypted by using special image division and additive homomorphic encryption. After image encryption, the encrypted image can partially maintain spatial correlation for data embedding while the content security of the encrypted image is ensured. Due to the spatial correlation, the data hider can generate two difference histograms from the encrypted image, which provide high embedding capacity. A two-phase histogram shift scheme is used to embed the secret data into the two difference histograms. At the receiver side, the secret data can be extracted from the encrypted image or the decrypted image, and the image can be recovered to its original version without any error. The experimental results demonstrated that the proposed method can efficiently improve the capacity of data embedding and outperform other related methods, while the visual quality of the marked image can be maintained.

With the popularity of outsourcing data to the cloud, it is vital to protect the privacy of data and enable the cloud server to easily manage the data at the same time. Under such demands, reversible data hiding in encrypted images (RDH-EI) attracts more and more researchers’ attention. In this paper, we propose a novel framework for RDH-EI based on reversible image transformation (RIT). Different from all previous encryption-based frameworks, in which the ciphertexts may attract the notation of the curious cloud, RIT-based framework allows the user to transform the content of original image into the content of another target image with the same size. The transformed image, that looks like the target image, is used as the “encrypted image,” and is outsourced to the cloud. Therefore, the cloud server can easily embed data into the “encrypted image” by any RDH methods for plaintext images. And thus a client-free scheme for RDH-EI can be realized, that is, the data-embedding process executed by the cloud server is irrelevant with the processes of both encryption and decryption. Two RDH methods, including traditional RDH scheme and unified embedding and scrambling scheme, are adopted to embed watermark in the encrypted image, which can satisfy different needs on image quality and large embedding capacity, respectively.

Reversible data hiding in encrypted images using adaptive reversible integer transformation

Reversible data hiding in encrypted images (RDHEI) has been introduced for preserving image privacy and data embedding. RDHEI usually involves three parties, namely, the image provider, data hider, and receiver. On the security with key setting, there are three categories: share independent secret keys (SIK), shared one key (SOK), and share no secret keys (SNK). In SIK, the image provider and data hider must respectively and independently share secret keys with the receiver, whereas in SNK, no secret key is shared. However, the literature works proposed SNK-type schemes by using homomorphic encryption (with exorbitant computation cost). In this paper, we address the SOK setting, where only the image provider shares a secret key with the receiver, and the data hider can embed a secret message without any knowledge of this key. To realize our SOK scheme in a simple manner, we propose a new technique by using multi-secret sharing as the underlying encryption, which indeed induces a blow-up issue of the key size. For preserving the efficiency of the key size, we apply a compression by using lightweight cryptographic algorithms. Then, we demonstrate our SOK scheme based on the proposed techniques, and show effectiveness, efficiency, and security by experiments and analysis.

This paper proposes an image retrieval approach in encrypted images that are outsourced to the cloud network using LSB (Least significant bit) elimination based feature extraction. To preserve the privacy of the image that is outsourced to the cloud, the images are encrypted. Retrieving the encrypted images that are outsourced to cloud is considered as a challenging task. The proposed method eliminates the LS B’ $s$ , and the histogram is estimated to obtain the necessary features. Initially, the image owner encrypts the original image by using a key and uploads the encrypted image to the cloud. The cloud server extracts the features from the encrypted original image and stores the features in the cloud. To perform image retrieval, the user has to encrypt the Query image using a key, and it must be uploaded to the cloud. The cloud server extracts the features from the Query image and matches with the features that are already stored in the cloud server. The encrypted images correspond to the top-k matched features are returned to the user, from which the user has to decrypt it using the key. The performance of the proposed method was measured in terms of Precision, time of feature extraction, time of index construction and time of image retrieval. Experimental results reveal that the proposed feature extraction outperforms than the traditional methods.

Steganography, a technique of data hiding, is becoming more and more significant with expansion of the Internet communication. As a result, various steganographic algorithms have been proposed in recent years, for example, Ni et al. have carried out a lossless data-hiding algorithm based on the histogram modification. In order to reinforce more security and more data embedding capacity, this paper extends the Ni's algorithm with a random permutation and a histogram re-quantization. To begin with, applying a random permutation, the security is not easy to be broken by a brute-force attack. In addition, the embedding capacity is able to be strengthened approximately 3 times by adopting a histogram re-quantization. As to our approach, it is visually indistinguishable between a cover image and a stegoimage with a large embedding capacity.

Existing prediction-based works on reversible data hiding in encrypted images usually embed the secret messages by referring to the difference between current pixel and its predicted value. An accurate prediction model may promote an improvement of embedding capacity. Existing schemes, however, may not work well due to involving a bad prediction model so that their embedding capacity cannot be improved further. To address the problem, this paper proposes a new reversible data hiding scheme in encrypted images by designing double linear regression prediction model. Proposed model can significantly improve the prediction accuracy of current pixel based on neighboring pixels, more auxiliary rooms are thus vacated to embed secret data. Furthermore, a prediction error map is constructed to mark the error positions caused by inaccurate prediction, which can be further compressed lossless to lower the capacity of auxiliary data. Reversible recovery for original image can be finally achieved successfully. Experimental results demonstrate that the proposed scheme significantly improves prediction accuracy and data embedding capacity by combining double linear regression prediction model and prediction error map, and then can achieve separable and lossless recovery for the original image. Compared with existing works, the proposed scheme can implement a higher visual quality of decrypted images, while maintaining a larger embedding capacity.

Popular cryptographic technology called Advanced Encryption Standard (AES) enables secure data transfer over the internet. It is used for a variety of purposes, such as secure data transfer, mobile phone encryption, and encryption of extremely sensitive data. It operates in terms of blocks, or chunks, of data. Steganography is the process of hiding data in another sort of data, such as a digital image. If a user wants to utilize a cryptographic method to conceal encrypted data in an image, such as AES, it is essential that the method be impervious to all possible attacks. This study has analyzed the possibility to hide data inside digital photos by utilizing encryption techniques like AES. The performance comparison of AES and Data Encryption Standard (DES), a full Python implementation of the AES for image steganography is also presented. To illustrate how each method performs, experimental results are provided. The Advanced Encryption Standard can be programmed in software or built with pure hardware.

The majority of imaging techniques use symmetric and asymmetric cryptography algorithms to encrypt digital media. Most of the research works contributed in the literature focus primarily on the Advanced Encryption Standard (AES) algorithm for encryption and decryption. This paper propose an analysis for performing image encryption and decryption by hybridization of Elliptic Curve Cryptography (ECC) with Hill Cipher (HC), ECC with Advanced Encryption Standard (AES) and ElGamal with Double Playfair Cipher (DPC). This analysis is based on the following parameters: (i) Encryption and decryption time, (ii) entropy of encrypted image, (iii) loss in intensity of the decrypted image, (iv) Peak Signal to Noise Ratio (PSNR), (v) Number of Pixels Change Rate (NPCR), and (vi) Unified Average Changing Intensity (UACI). The hybrid process involves the speed and ease of implementation from symmetric algorithms, as well as improved security from asymmetric algorithms. ECC and ElGamal cryptosystems provide asymmetric key cryptography, while HC, AES, and DPC are symmetric key algorithms. ECC with AES are perfect for remote or private communications with smaller image sizes based on the amount of time needed for encryption and decryption. The metric measurement with test cases finds that ECC and HC have a good overall solution for image encryption.

One of the universally studied research topics is a reversible data hiding approach because of its wide applications in medical image transmission, cloud computing as well as in military services. In the introduced scheme stated in this paper, a new RDH scheme in encrypted images is proposed which ensures a good embedding rate without compromising the bit error rate. The scheme introduced in this manuscript uses a new measure that is computationally efficient and ensures real-time performance. In the proposed scheme, the original image is divided into blocks and in each block, one secret message bit is hidden by the data hider. All the pixels in the image block are categorized into two classes: black pixels and white pixels based on the predefined checkerboard pattern. The data hiding is performed by mapping the pixel values in the white position to a new value, only if the data hider wants to hide a secret bit 1. At the time of data extraction and image recovery, the closeness between the adjacent pixels is analyzed by considering a pair of adjacent black pixels and white pixels from the quantized image blocks. The overall experimental study of the proposed scheme is carried out using the standard images from the USC-SIPI image dataset managed by the University of Southern California.

Secure image transmission is one of the most challenging problems in the age of communication technology. Millions of people use and transfer images for either personal or commercial purposes over the internet. One way of achieving secure image transmission over the network is encryption techniques that convert the original image into a non-understandable or scrambled form, called a cipher image, so that even if the attacker gets access to the cipher they would not be able to retrieve the original image. In this study, chaos-based image encryption and block cipher techniques are implemented and analyzed for image encryption. Arnold cat map in combination with a logistic map are used as native chaotic and hybrid chaotic approaches respectively whereas advanced encryption standard (AES) is used as a block cipher approach. The chaotic and AES methods are applied to encrypt images and are subjected to measures of different performance parameters such as peak signal to noise ratio (PSNR), number of pixels change rate (NPCR), unified average changing intensity (UACI), and histogram and computation time analysis to measure the strength of each algorithm. The results show that the hybrid chaotic map has better NPCR and UACI values which makes it more robust to differential attacks or chosen plain text attacks. The Arnold cat map is computationally efficient in comparison to the other two approaches. However, AES has a lower PSNR value (7.53 to 11.93) and has more variation between histograms of original and cipher images, thereby indicating that it is more resistant to statistical attacks than the other two approaches.

Reversible data hiding in encrypted images using Pixel Shifting Approach (PSA)

Satellite images have key features such as; large data size, strong correlation between adjacent pixels and high redundancy. Unfortunately, traditional operation modes used to implement the Advanced Encryption Standard (AES) encrypt data without taking into account these specific image features. As a result, the traditional modes are not suitable for image encryption. In this paper, we present a robust satellite image encryption scheme based on discretized chaotic maps and AES. The discretized chaotic maps are used to achieve a confusion and key generation in order to improve the performance of security, especially the sensitivity to plain image. The simulation results show that the proposed technique presents attractive features, including a high level of security, large key space with improved sensitivities to key and plain image.

Adaptive embedding combining LBE and IBBE for high-capacity reversible data hiding in encrypted images

Steganography is a data hiding process in which information is secured, while transferring data from sender to receiver. In audio steganography, encoding process is carried nut through inactive frames of low bit rate audio streams by performing iLBC (internet Low Bit rate Codec). This methodology can be used in applications such as VoIP (Voice Over Internet Protocol), streaming audio, archival and messaging. Traditionally, data embedding is carried out in the inactive frames rather than the active frame of streams; that is inactive frame has large embedding capacity. In addition VAD (Voice Activity Detection) algorithm is used for detecting inactive frames. The concealment of analysis is encoded by iLBC, that supports two basic frame lengths, giving a bit-rate of 13.3 kbps with an encoding frame length of 30 ms and 15.2 kbps with an encoding frame length of 20 nis . To enhance security in steganography PCC (Parabolic Curve Cryptography) algorithm is implemented.