A survey of big data management

Internet of Medical Things (IoMT) can connect many medical imaging equipment to the medical information network to facilitate the process of diagnosing and treating doctors. As medical image contains sensitive information, it is of importance yet very challenging to safeguard the privacy or security of the patient. In this work, a deep-learning-based image encryption and decryption network (DeepEDN) is proposed to fulfill the process of encrypting and decrypting the medical image. Specifically, in DeepEDN, the cycle-generative adversarial network (Cycle-GAN) is employed as the main learning network to transfer the medical image from its original domain into the target domain. The target domain is regarded as “hidden factors” to guide the learning model for realizing the encryption. The encrypted image is restored to the original (plaintext) image through a reconstruction network to achieve image decryption. In order to facilitate the data mining directly from the privacy-protected environment, a region of interest (ROI)-mining network is proposed to extract the interesting object from the encrypted image. The proposed DeepEDN is evaluated on the chest X-ray data set. Extensive experimental results and security analysis show that the proposed method can achieve a high level of security with a good performance in efficiency.

DeepEDN: A Deep-Learning-Based Image Encryption and Decryption Network for Internet of Medical Things

Security of data/images is one of the crucial aspects in the gigantic and still expanding domain of digital transfer. Encryption of images is one of the well known mechanisms to preserve confidentiality of images over a reliable unrestricted public media. This medium is vulnerable to attacks and hence efficient encryption algorithms are necessity for secure data transfer. Various techniques have been proposed in literature till date, each have an edge over the other, to catch-up to the ever growing need of security. This paper is an effort to compare the most popular techniques available on the basis of various performance metrics like differential, statistical and quantitative attacks analysis. To measure the efficacy, all the modern and grown-up techniques are implemented in MATLAB-2015. The results show that the chaotic schemes used in the study provide highly scrambled encrypted images having uniform histogram distribution. In addition, the encrypted images provided very less degree of correlation coefficient values in horizontal, vertical and diagonal directions, proving their resistance against statistical attacks. In addition, these schemes are able to resist differential attacks as these showed a high sensitivity for the initial conditions, i.e. pixel and key values. Finally, the schemes provide a large key spacing, hence can resist the brute force attacks, and provided a very less computational time for image encryption/decryption in comparison to other schemes available in literature.

A Survey of Image Encryption Algorithms

The need for image encryption is constantly on the rise and has led to the emergence of many techniques in literature. In recent years, many chaos-based encryption techniques have developed with more or less success. In this study, we suggest one such approach using two oscillators. Mixed chaotic maps from the Colpitts and Duffing oscillators were used to encrypt images, which helped to increase the key space to 2448 ≃ 7.26 × 10134. The authors also succeeded to reduce the encryption time by saving the mixed chaotic maps and reusing them as need arose. The proposed system was tested on well-known images like Lena, NebulaM83, Mandrill and Clown.

Image encryption by chaos mixing

Based blockchain-PSO-AES techniques in finger vein biometrics: A novel verification secure framework for patient authentication

In recent years, encryption technology has been developed quickly and many image encryption methods have been put forward. Chaos based image encryption technique is a new encryption technique for images. It utilizes chaos random sequence to encrypt image, which is an efficient way to deal with the intractable problem of fast and highly secure image encryption. However, the Chaos based image encryption technique has some deficiencies, such as the limited accuracy problem. This paper researches on the chaotic encryption, DES encryption and a combination of image encryption algorithm, and simulate these algorithms, through analysis of the algorithm to find the gaps. And on this basis, the algorithm has been improved. The new encryption scheme realizes the digital image encryption through the chaos and improving DES. Firstly, new encryption scheme uses the Logistic chaos sequencer to make the pseudo-random sequence, carries on the RGB with this sequence to the image chaotically, then makes double time encryptions with improvement DES, displays they respective merit. Theoretical analysis and the simulation indicate that this plan has the high starting value sensitivity, and enjoys high security and the encryption speed. In addition it also keeps the neighboring RGB relevance close to zero. The algorithm can be used in the actual image encryption.

Nie Xuan

Papers

Digital image encryption algorithm based on chaos and improved DES

PDDS: A software for the early diagnosis of Parkinson’s disease from MRI and DaT scan images using detection and segmentation algorithms