46 research outputs found

    Research on digital image watermark encryption based on hyperchaos

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    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

    Lightweight image encryption algorithms: design and evaluation

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    Doctor of PhilosophyDepartment of Computer ScienceArslan MunirIn an era dominated by increasing use of multimedia data such as images and videos, ensuring the security and confidentiality of images with real-time encryption is of greatest importance. Traditional encryption algorithms are secure, widely used, and recommended, yet they are not suitable nor computationally efficient for encrypting multimedia data due to the large size and high redundancy inherent in multimedia data. Thus, specialized algorithms for multimedia data encryption are needed. This dissertation explores lightweight image encryption algorithms, specifically designed to address time and resource constraints of realtime image encryption while maintaining the confidentiality and integrity of the multimedia data. The dissertation classifies image encryption based on the techniques used into seven different approaches and analyzes the strengths and weaknesses of each approach. It subsequently introduces and evaluates three novel algorithms designed to encrypt images with low complexity, high efficiency, and reliable security. These algorithms rely on a combination of permutation, substitution, and pseudorandom keystreams to ensure the security of the encrypted images. The first algorithm is based on chaotic systems. The algorithm is implemented using logistic map, permutations, AES S-box, and a plaintext related SHA-2 hash. The second algorithm is based on Trivium cipher. the algorithm is implemented to work on multi-rounds of encryption using pixel-based row and column permutations, and bit-level substitution. For the third algorithm, the Ascon algorithm selected by the National Institute of Standards and Technology (NIST) to standardize lightweight cryptography applications is evaluated for image encryption. To evaluate the proposed algorithms, a comprehensive set of security, quality, and efficiency valuation metrics is utilized to assess the proposed algorithms and compare them to contemporary image encryption algorithms

    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

    An efficient quantum-classical hybrid algorithm for distorted alphanumeric character identification

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    An algorithm for image processing is proposed. The proposed algorithm, which can be viewed as a quantum-classical hybrid algorithm, can transform a low-resolution bitonal image of a character from the set of alphanumeric characters (A-Z, 0-9) into a high-resolution image. The quantum part of the proposed algorithm fruitfully utilizes a variant of Grover's search algorithm, known as the fixed point search algorithm. Further, the quantum part of the algorithm is simulated using CQASM and the advantage of the algorithm is established through the complexity analysis. Additional analysis has also revealed that this scheme for optical character recognition (OCR) leads to high confidence value and generally works in a more efficient manner compared to the existing classical, quantum, and hybrid algorithms for a similar task.Comment: A quantum-assisted algorithm for optical character recognition (OCR) is proposed using fixed point Grover's algorith
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