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The swift growth of communication facilities and ever decreasing cost of computer hardware has brought tremendous possibilities of expansion for commercial and academic rationales. With widely incremented communiqué like Internet, not only the good guys, but also bad guys have advantage. The hackers or crackers can take advantage of network vulnera...
Citations
... The insufficient mix of chaotic elements and encryption [11,12] structures makes the unpredictability of recouping its secret key, from a few sets of plain-writings and the relating cipher-texts, encrypted with a similar secret key, lower than that of the brutal force attack [13]. The patient's name straightforwardly being connected with the image is observed as imperative from the patient's perspective [31] and keeping that data secret [14], is vital for the consistency with image [15]. ...
With the rapid development in the field of medical image encryption, researchers analyzed a number of encryption algorithms based on chaotic systems. But there is a difficulty lies i.e., small key space and weak security in one-dimensional chaotic cryptosystems. To overcome this difficulty, an alternative security model was proposed in this paper. The current study investigated highly secure medical images with a couple of subkeys, initially where a couple of subkeys is given by utilizing chaotic logistic and tent maps. As per the Chaotic (C - function) process, the security was investigated like diffusion as well as confusion. Based on the initial conditions, different random numbers were generated for each map from chaotic maps. Adaptive Grasshopper Optimization (AGO) algorithm with PSNR and CC fitness function was proposed to choose the optimal secret and public key of the system among the random numbers. The reason behind choosing adaptive process is to enhance high-security investigation of the current proposed model compared to existing methods. At last, the proposed strategy results were compared with existing security methods and literary works, but found to be high performing.
... This is why asymmetric cryptography is considered more secure than symmetric cryptography [Harris 2012]. Some of the contributions in this field can be found in the following works [Wang et al. 2008;Ding and Jing 2010;Zhu et al. 2010;Kaushik et al. 2014;Zhang and Ding 2015]. ...
In this article, a detailed survey of the quantum approach to image processing is presented. Recently, it has been established that existing quantum algorithms are applicable to image processing tasks allowing quantum informational models of classical image processing. However, efforts continue in identifying the diversity of its applicability in various image processing domains. Here, in addition to reviewing some of the critical image processing applications that quantum mechanics have targeted, such as denoising, edge detection, image storage, retrieval, and compression, this study will also highlight the complexities in transitioning from the classical to the quantum domain. This article shall establish theoretical fundamentals, analyze performance and evaluation, draw key statistical evidence to support claims, and provide recommendations based on published literature mostly during the period from 2010 to 2015.
Visual Cryptography (VC) is a process employed for the maintenance of secret information by hiding the secret messages that are embedded within the images. Typically, an image is partitioned into a number of shares that are stacked over one another in order to reconstruct back the original image accurately. The major limitation that existed in the traditional VC techniques is pixel expansion, in which pixel expansion is replaced with a number of sub-pixels in individual share, which causes a considerable impact on the contrast and resolution of the image that further gradually decreases the quality of the image. VC is named for its essential characteristics, such as transmitting the images with two or more shares with an equal number of black pixels and color pixel distribution. The secret message can be decrypted using Human Visual System (HVS). In this paper, 50 research papers are reviewed based on various classification algorithms, which are effectively used for the VC technique. The classification algorithms are categorized into three types, namely, meta-heuristic, heuristic, and evolutionary, and the research issues and challenges confronted by the existing techniques are reported in this survey. Moreover, the analysis is done based on the existing research works by considering the classification algorithms, tools, and evaluation metrics.
