Color image encryption based on chaotic shit keying with lossless compression

In order to protect valuable data from undesirable readers or against illegal reproduction and modifications, there have been various data encryption techniques. Many methods are developed to perform image encryption. The use of chaotic map for image encryption is very effective, since it increase the security, due to its random behavior. The most attractive feature of deterministic chaotic systems is he extremely unexpected and random-look nature of chaotic signals that may lead to novel applications. A novel image encryption algorithm based on compression and hyper chaotic map techniques is proposed. Firstly the image is decomposed into three subbands R, G, and B then each band is compressed using lossless technique. The generated chaotic sequences from the 3D chaotic system are employed to code the compressed results by employing the idea of chaotic shift encoding (CSK) modulation to encode the three bands to generate the encrypted image. The experiments show that the proposed method give good results in term of security, feasibility, and robustness

Discrete Wavelet Transform based Cryptosystem

In this article, the authors proposed, implemented and analysed a symmetric key cryptographic algorithm that can be considered as a lossless encryption and decryption technique, advantageous especially in situations where, even a slight marginal distortion is not tolerable. In the proposed system, Haar wavelet is used initially, to transform the original target image into its frequency domain, followed by  encrypting the resulting sub-bands, so as to obtain a secure and reliable encrypted image. The resulting coefficients after Haar decomposition is scattered using a reversible weighing factor, suitably reversed and swapped to get the secure encrypted image. The encrypted image is  then correspondingly decrypted, by the reverse process to get back the original decrypted image. Statistical testing and security methods were used to evaluate and analyse the proposed cryptosystem and the results showed that the proposed system is cryptographically resistant to attacks and is also highly secure when compared to other cryptographic systems in the frequency domain

Hybrid chaotic map with L-shaped fractal Tromino for image encryption and decryption

Insecure communication in digital image security and image storing are considered as important challenges. Moreover, the existing approaches face problems related to improper security at the time of image encryption and decryption. In this research work, a wavelet environment is obtained by transforming the cover image utilizing integer wavelet transform (IWT) and hybrid discrete cosine transform (DCT) to completely prevent false errors. Then the proposed hybrid chaotic map with L-shaped fractal Tromino offers better security to maintain image secrecy by means of encryption and decryption. The proposed work uses fractal encryption with the combination of L-shaped Tromino theorem for enhancement of information hiding. The regions of L-shaped fractal Tromino are sensitive to variations, thus are embedded in the watermark based on a visual watermarking technique known as reversible watermarking. The experimental results showed that the proposed method obtained peak signal-to-noise ratio (PSNR) value of 56.82dB which is comparatively higher than the existing methods that are, Beddington, free, and Lawton (BFL) map with PSNR value of 8.10 dB, permutation substitution, and Boolean operation with PSNR value of 21.19 dB and deoxyribonucleic acid (DNA) level permutation-based logistic map with PSNR value of 21.27 dB

Enhanced image encryption scheme with new mapreduce approach for big size images

Achieving a secured image encryption (IES) scheme for sensitive and confidential data communications, especially in a Hadoop environment is challenging. An accurate and secure cryptosystem for colour images requires the generation of intricate secret keys that protect the images from diverse attacks. To attain such a goal, this work proposed an improved shuffled confusion-diffusion based colour IES using a hyper-chaotic plain image. First, five different sequences of random numbers were generated. Then, two of the sequences were used to shuffle the image pixels and bits, while the remaining three were used to XOR the values of the image pixels. Performance of the developed IES was evaluated in terms of various measures such as key space size, correlation coefficient, entropy, mean squared error (MSE), peak signal to noise ratio (PSNR) and differential analysis. Values of correlation coefficient (0.000732), entropy (7.9997), PSNR (7.61), and MSE (11258) were determined to be better (against various attacks) compared to current existing techniques. The IES developed in this study was found to have outperformed other comparable cryptosystems. It is thus asserted that the developed IES can be advantageous for encrypting big data sets on parallel machines. Additionally, the developed IES was also implemented on a Hadoop environment using MapReduce to evaluate its performance against known attacks. In this process, the given image was first divided and characterized in a key-value format. Next, the Map function was invoked for every key-value pair by implementing a mapper. The Map function was used to process data splits, represented in the form of key-value pairs in parallel modes without any communication between other map processes. The Map function processed a series of key/value pairs and subsequently generated zero or more key/value pairs. Furthermore, the Map function also divided the input image into partitions before generating the secret key and XOR matrix. The secret key and XOR matrix were exploited to encrypt the image. The Reduce function merged the resultant images from the Map tasks in producing the final image. Furthermore, the value of PSNR did not exceed 7.61 when the developed IES was evaluated against known attacks for both the standard dataset and big data size images. As can be seen, the correlation coefficient value of the developed IES did not exceed 0.000732. As the handling of big data size images is different from that of standard data size images, findings of this study suggest that the developed IES could be most beneficial for big data and big size images

Balancing Compression and Encryption of Satellite Imagery

With the rapid developments in the remote sensing technologies and services, there is a necessity for combined compression and encryption of satellite imagery. The onboard satellite compression is used to minimize storage and communication bandwidth requirements of high data rate satellite applications. While encryption is employed to secure these resources and prevent illegal use of image sensitive information. In this paper, we propose an approach to address these challenges which raised in the highly dynamic satellite based networked environment. This approach combined compression algorithms (Huffman and SPIHT) and encryptions algorithms (RC4, blowfish and AES) into three complementary modes: (1) secure lossless compression, (2) secure lossy compression and (3) secure hybrid compression. The extensive experiments on the 126 satellite images dataset showed that our approach outperforms traditional and state of art approaches by saving approximately (53%) of computational resources. In addition, the interesting feature of this approach is these three options that mimic reality by imposing every time a different approach to deal with the problem of limited computing and communication resources

Research on digital image watermark encryption based on hyperchaos

The digital watermarking technique embeds meaningful information into one or more watermark images hidden in one image, in which it is known as a secret carrier. It is difficult for a hacker to extract or remove any hidden watermark from an image, and especially to crack so called digital watermark. The combination of digital watermarking technique and traditional image encryption technique is able to greatly improve anti-hacking capability, which suggests it is a good method for keeping the integrity of the original image. The research works contained in this thesis include: (1)A literature review the hyperchaotic watermarking technique is relatively more advantageous, and becomes the main subject in this programme. (2)The theoretical foundation of watermarking technologies, including the human visual system (HVS), the colour space transform, discrete wavelet transform (DWT), the main watermark embedding algorithms, and the mainstream methods for improving watermark robustness and for evaluating watermark embedding performance. (3) The devised hyperchaotic scrambling technique it has been applied to colour image watermark that helps to improve the image encryption and anti-cracking capabilities. The experiments in this research prove the robustness and some other advantages of the invented technique. This thesis focuses on combining the chaotic scrambling and wavelet watermark embedding to achieve a hyperchaotic digital watermark to encrypt digital products, with the human visual system (HVS) and other factors taken into account. This research is of significant importance and has industrial application value

Authenticated public key elliptic curve based on deep convolutional neural network for cybersecurity image encryption application

The demand for cybersecurity is growing to safeguard information flow and enhance data privacy. This essay suggests a novel authenticated public key elliptic curve based on a deep convolutional neural network (APK-EC-DCNN) for cybersecurity image encryption application. The public key elliptic curve discrete logarithmic problem (EC-DLP) is used for elliptic curve Diffie–Hellman key exchange (EC-DHKE) in order to generate a shared session key, which is used as the chaotic system’s beginning conditions and control parameters. In addition, the authenticity and confidentiality can be archived based on ECC to share the (Formula presented.) parameters between two parties by using the EC-DHKE algorithm. Moreover, the 3D Quantum Chaotic Logistic Map (3D QCLM) has an extremely chaotic behavior of the bifurcation diagram and high Lyapunov exponent, which can be used in high-level security. In addition, in order to achieve the authentication property, the secure hash function uses the output sequence of the DCNN and the output sequence of the 3D QCLM in the proposed authenticated expansion diffusion matrix (AEDM). Finally, partial frequency domain encryption (PFDE) technique is achieved by using the discrete wavelet transform in order to satisfy the robustness and fast encryption process. Simulation results and security analysis demonstrate that the proposed encryption algorithm achieved the performance of the state-of-the-art techniques in terms of quality, security, and robustness against noise- and signal-processing attacks

Classification of novel selected region of interest for color image encryption

Securing digital image in exchanging huge multimedia data over internet with limited bandwidth is a significant and sensitive issue. Selective image encryption being an effective method for reducing the amount of encrypted data can achieve adequate security enhancement. Determining and selecting the region of interest in digital color images is challenging for selective image encryption due to their complex structure and distinct regions of varying importance. We propose a new feature in acquiring and selecting Region of Interest (ROI) for the color images to develop a selective encryption scheme. The hybrid domain is used to encrypt regions based on chaotic map approach which automatically generates secret key. This new attribute is a vitality facet representing the noteworthy part of the color image. The security performance of selective image encryption is found to enhance considerably based on the rates of encrypted area selection. Computation is performed using MATLAB R2008a codes on eight images (Lena, Pepper, Splash, Airplane, House, Tiffany, Baboon and Sailboat) each of size 512*512 pixels obtained from standard USC-SIPI Image Database. A block size of 128*128 pixels with threshold levels 0.0017 and 0.48 are employed. Results are analyzed and compared with edge detection method using the same algorithm. Encrypted area, entropy and correlation coefficients performances reveal that the proposed scheme achieves good alternative in the confined region of interest, fulfills the desired confidentiality and protects image privacy