61 research outputs found

    DNA key based visual chaotic image encryption

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    With the exponential growth of Internet technologies, digital information exchanged over the Internet is also significantly increased. In order to ensure the security of multimedia contents over the open natured Internet, data should be encrypted. In this paper, the quantum chaotic map is utilized for random vectors generation. Initial conditions for the chaos map are computed from a DNA (Deoxyribonucleic acid) sequence along with plaintext image through Secure Hash Algorithm-512 (SHA-512). The first two random vectors break the correlation among pixels of the original plaintext image via row and column permutation, respectively. For the diffusion characteristics, the permuted image is bitwise XORed with a random matrix generated through the third random vectors. The diffused image is divided into Least Significant Bit (LSB) and Most Significant Bits (MSBs) and Discrete Wavelet Transform (DWT) is applied to the carrier image. The HL and HH blocks of the carrier image are replaced with LSBs and MSBs of the diffused image for the generation of a visually encrypted image. The detailed theoretical analysis and experimental simulation of the designed scheme show that the proposed encryption algorithm is highly secured. Efficiency and robustness of the proposed visually image encryption scheme is also verified via a number of attack analyses, i.e., sensitivity attack analysis (> 99%), differential attack analysis (NPCR > 99, UACI > 33), brute force attack (almost 7.9892), statistical attack (correlation coefficient values are almost 0 or less than zero), noise tolerance, and cropping attack. Further security analyses such as encryption quality (ID ≅ 1564, DH = 3.000), homogeneity (0.3798), contrast (10.4820) and energy (0.0144) of the scheme are also evaluated

    Preserving Trustworthiness and Confidentiality for Online Multimedia

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    Technology advancements in areas of mobile computing, social networks, and cloud computing have rapidly changed the way we communicate and interact. The wide adoption of media-oriented mobile devices such as smartphones and tablets enables people to capture information in various media formats, and offers them a rich platform for media consumption. The proliferation of online services and social networks makes it possible to store personal multimedia collection online and share them with family and friends anytime anywhere. Considering the increasing impact of digital multimedia and the trend of cloud computing, this dissertation explores the problem of how to evaluate trustworthiness and preserve confidentiality of online multimedia data. The dissertation consists of two parts. The first part examines the problem of evaluating trustworthiness of multimedia data distributed online. Given the digital nature of multimedia data, editing and tampering of the multimedia content becomes very easy. Therefore, it is important to analyze and reveal the processing history of a multimedia document in order to evaluate its trustworthiness. We propose a new forensic technique called ``Forensic Hash", which draws synergy between two related research areas of image hashing and non-reference multimedia forensics. A forensic hash is a compact signature capturing important information from the original multimedia document to assist forensic analysis and reveal processing history of a multimedia document under question. Our proposed technique is shown to have the advantage of being compact and offering efficient and accurate analysis to forensic questions that cannot be easily answered by convention forensic techniques. The answers that we obtain from the forensic hash provide valuable information on the trustworthiness of online multimedia data. The second part of this dissertation addresses the confidentiality issue of multimedia data stored with online services. The emerging cloud computing paradigm makes it attractive to store private multimedia data online for easy access and sharing. However, the potential of cloud services cannot be fully reached unless the issue of how to preserve confidentiality of sensitive data stored in the cloud is addressed. In this dissertation, we explore techniques that enable confidentiality-preserving search of encrypted multimedia, which can play a critical role in secure online multimedia services. Techniques from image processing, information retrieval, and cryptography are jointly and strategically applied to allow efficient rank-ordered search over encrypted multimedia database and at the same time preserve data confidentiality against malicious intruders and service providers. We demonstrate high efficiency and accuracy of the proposed techniques and provide a quantitative comparative study with conventional techniques based on heavy-weight cryptography primitives

    Entropy in Image Analysis II

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    Image analysis is a fundamental task for any application where extracting information from images is required. The analysis requires highly sophisticated numerical and analytical methods, particularly for those applications in medicine, security, and other fields where the results of the processing consist of data of vital importance. This fact is evident from all the articles composing the Special Issue "Entropy in Image Analysis II", in which the authors used widely tested methods to verify their results. In the process of reading the present volume, the reader will appreciate the richness of their methods and applications, in particular for medical imaging and image security, and a remarkable cross-fertilization among the proposed research areas

    Irish Machine Vision and Image Processing Conference Proceedings 2017

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    Entropy in Image Analysis III

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    Image analysis can be applied to rich and assorted scenarios; therefore, the aim of this recent research field is not only to mimic the human vision system. Image analysis is the main methods that computers are using today, and there is body of knowledge that they will be able to manage in a totally unsupervised manner in future, thanks to their artificial intelligence. The articles published in the book clearly show such a future

    18th SC@RUG 2020 proceedings 2020-2021

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    18th SC@RUG 2020 proceedings 2020-2021

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