Development of Scalable Coding of Encrypted Images Using Modified Absolute Moment Block Truncation Code

Many researchers worked on scalable coding for unencrypted images, and there is more space for research in scalable coding for encrypted images. This paper proposes a novel method of scalable coding for encrypted images, especially for lossy compression images using the Modified Absolute Moment Block Truncation Code (MAMBTC) technique. The given input image is compressed using MAMBTC and then encrypted using a Pseudo-Random Number (PRNG) at the encryption phase. The PRNG is shared between the encoder and the decoder. At the decryption phase, the compressed pixel value is obtained by decryption using the PRNG and then reconstructed using MAMBTC, scaled by scaling factor 2 and Bilinear Interpolation Technique to obtain the original image. MAMBTC gives better image quality than Block Truncation Code (BTC), a higher PSNR of 36.32 dB, and a Compression ratio of 1.09, which makes the proposed system ready for the signal processing community/applications.

A New IOT Image Encryption Algorithm based on Chaotic Map

IOT information is always subjected to attacks, because component of the IOT system always unsupervised for most of time, also due to simplicity of wireless communication media, so there is high chance for attack, lastly, IOT is constraint device in terms of energy and computation complexity. So, different research and study are proposed to provide cryptographic algorithm. In this paper, a new image encryption is proposed based on anew chaotic map used to generate the binary key. The proposed map is three dimensional map, which is more sensitive to initial condition, each dimension of the 3-D chaotic map is depended on the others dimension, which may increase the randomness of the behavior trajectory for the next values and this gives the algorithm the ability to resist any attacks. At first, 3-D chaotic map is proposed, which is very sensitive for initial condition, the three dimension is depended on each other, which make the system more randomness, then the produced sequences is converted on binary key by using mod operation. The original image is scrambled based on mod operation to exchange the row and interleaving them, the same operations are repeated for column of the image. Later, the image is divided into blocks of size (8*8) and scrambled by using negative diagonal scan, the final pixels are converted into binary sequences, which are XORed with the generated key to produce the encrypted image. The experiment is performed on different images with different properties and tested with different metrics such as entropy, correlation, key sensitivity, number of pixel change rate (NPCR) and histogram of the original and encrypted images. T results shows that the proposed encryption algorithm is more efficient and outperform other methods.

Reversible Information of Encrypted Image Based on Feature Difference Detection and Wavelet Transform

Aiming at the shortcomings of the existing lossless digital watermarking algorithm based on frequency domain in reversibility and embedding capacity, this study proposes a lossless digital image watermarking algorithm based on fractional wavelet transform, which is used for large-capacity reversible information hiding of images. First, the image is transformed by LeGall5/3 fractional wavelet, and then, the watermark is embedded in the high-frequency subband by the histogram shift method. In order to obtain maximum embedding capacity and reduce image distortion, the methods of selecting embedding parameters and stopping parameters are proposed, respectively. At the same time, in order to prevent overflow and reduce additional information, a new method of generating position map is proposed. The experimental results show that Lena is the result of multilayer embedding based on the algorithm in this study. In order to better observe the distortion phenomenon and enlarge the image, the Lena test image is the watermark image obtained after two and three layers of embedding, and its embedding capacity can be 2.7 bpp. It is proved that wavelet transform is suitable for encrypted images to implement covert communication.

Applying GMEI-GAN to Generate Meaningful Encrypted Images in Reversible Data Hiding Techniques

With the rapid development of information technology, the transmission of information has become convenient. In order to prevent the leakage of information, information security should be valued. Therefore, the data hiding technique has become a popular solution. The reversible data hiding technique (RDH) in particular uses symmetric encoding and decoding algorithms to embed the data into the cover carrier. Not only can the secret data be transmitted without being detected and retrieved completely, but the cover carrier also can be recovered without distortion. Moreover, the encryption technique can protect the carrier and the hidden data. However, the encrypted carrier is a form of ciphertext, which has a strong probability to attract the attention of potential attackers. Thus, this paper uses the generative adversarial networks (GAN) to generate meaningful encrypted images for RDH. A four-stage network architecture is designed for the experiment, including the hiding network, the encryption/decryption network, the extractor, and the recovery network. In the hiding network, the secret data are embedded into the cover image through residual learning. In the encryption/decryption network, the cover image is encrypted into a meaningful image, called the marked image, through GMEI-GAN, and then the marked image is restored to the decrypted image via the same architecture. In the extractor, 100% of the secret data are extracted through the residual learning framework, same as the hiding network. Lastly, in the recovery network, the cover image is reconstructed with the decrypted image and the retrieved secret data through the convolutional neural network. The experimental results show that using the PSNR/SSIM as the criteria, the stego image reaches 45.09 dB/0.9936 and the marked image achieves 38.57 dB/0.9654. The proposed method not only increases the embedding capacity but also maintains high image quality in the stego images and marked images.

Efficient Transmission of 2D Chaotic Maps Encrypted Images with DWT-Based SC-FDMA LTE System

The single-carrier frequency division multiple access (SC-FDMA) is a promising technique that has been adopted as an uplink transmission scheme in the long-term evolution (LTE) cellular system. This is attributed to its advantages such as the low peak-to-average power ratio (PAPR) and the utilization of frequency-domain equalizers to resolve the problem of inter-symbol interference (ISI). In this paper, a Discrete Wavelet Transform (DWT) based SC-FDMA system is proposed for the effective transmission of encrypted images. The 2D Chaotic baker map encryption algorithm has been used to encrypt images to enhance their security during transmission via SC-FDMA- based systems. The performance of the process of encrypted image transmission using the 2D Chaotic baker map algorithm with wavelet transform-based SC-FDMA (DWT SC-FDMA) system is evaluated in terms of different performance metrics, with comparison to Discrete Fourier Transform SC-FDMA (DFT SC-FDMA) and, Discrete Cosine Transform SC-FDMA (DCT SC-FDMA) systems. The viability of the proposed scheme was tested with different wireless channel models and different subcarriers mapping schemes. Experimental results show that the proposed method of the encrypted image transmission via the DWT SC-FDMA system provides a remarkable performance gain compared to the other versions of the SC-FDMA system in terms of the PSNR, and the BER metrics in the wireless channel models. It also demonstrates the effectiveness of the proposed scheme and adds a degree of encryption to the transmitted images through the wireless channels.

A Reversible Data Hiding Method in Encrypted Images for Controlling Trade-Off between Hiding Capacity and Compression Efficiency

In this paper, we propose a new framework for reversible data hiding in encrypted images, where both the hiding capacity and lossless compression efficiency are flexibly controlled. There exist two main purposes; one is to provide highly efficient lossless compression under a required hiding capacity, while the other is to enable us to extract an embedded payload from a decrypted image. The proposed method can decrypt marked encrypted images without data extraction and derive marked images. An original image is arbitrarily divided into two regions. Two different methods for reversible data hiding in encrypted images (RDH-EI) are used in our method, and each one is used for either region. Consequently, one region can be decrypted without data extraction and also losslessly compressed using image coding standards even after the processing. The other region possesses a significantly high hiding rate, around 1 bpp. Experimental results show the effectiveness of the proposed method in terms of hiding capacity and lossless compression efficiency.