Digital image watermarking is a technique adopted to get rid of the increasing piracies in digital images. Computerized information can be effectively duplicated, altered and falsifications be made by anybody having a PC. Most inclined to such vindictive assaults are the watermarked pictures distributed in the Internet. Advanced Watermarking can be utilized as a device for finding unapproved information reuse and furthermore for copyright security. In the existing method, texturization dependant image watermarking methodology is performed which involves the embedding and extraction of a logo image to and from an original image respectively. After finding out the texture regions of host image, the logo image is embedded into the identified texture regions by Discrete Wavelet Transform. Before embedding, according to the textual characteristics of the host image analyzed, texturization of a logo is done by using Arnold transform and a rotation. It is effective for attaining a similar texture for both logo image and host image. Later the logo image is extracted back. Discrete Wavelet Transform results in degradation of quality and robustness of watermarked image. Also it is not a difficult task for an attacker to compromise the Arnold transform and rotation performed. In this work, Lifting Wavelet Transform technique is used instead of the Discrete Wavelet Transform as it overcome the above mentioned drawback. In addition, Arnold transform and rotation is replaced with circular shift method for enhancing security.

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The industry-based internet of things (IIoT) describes how IIoT devices enhance and extend their capabilities for production amenities, security, and efficacy. IIoT establishes an enterprise-to-enterprise setup that means industries have several factories and manufacturing units that are dependent on other sectors for their services and products. In this context, individual industries need to share their information with other external sectors in a shared environment which may not be secure. The capability to examine and inspect such large-scale information and perform analytical protection over the large volumes of personal and organizational information demands authentication and confidentiality so that the total data are not endangered after illegal access by hackers and other unauthorized persons. In parallel, these large volumes of confidential industrial data need to be processed within reasonable time for effective deliverables. Currently, there are many mathematical-based symmetric and asymmetric key cryptographic approaches and identity- and attribute-based public key cryptographic approaches that exist to address the abovementioned concerns and limitations such as computational overheads and taking more time for crucial generation as part of the encipherment and decipherment process for large-scale data privacy and security. In addition, the required key for the encipherment and decipherment process may be generated by a third party which may be compromised and lead to man-in-the-middle attacks, brute force attacks, etc. In parallel, there are some other quantum key distribution approaches available to produce keys for the encipherment and decipherment process without the need for a third party. However, there are still some attacks such as photon number splitting attacks and faked state attacks that may be possible with these existing QKD approaches. The primary motivation of our work is to address and avoid such abovementioned existing problems with better and optimal computational overhead for key generation, encipherment, and the decipherment process compared to the existing conventional models. To overcome the existing problems, we proposed a novel dynamic quantum key distribution (QKD) algorithm for critical public infrastructure, which will secure all cyber–physical systems as part of IIoT. In this paper, we used novel multi-state qubit representation to support enhanced dynamic, chaotic quantum key generation with high efficiency and low computational overhead. Our proposed QKD algorithm can create a chaotic set of qubits that act as a part of session-wise dynamic keys used to encipher the IIoT-based large scales of information for secure communication and distribution of sensitive information.

Cloud computing is a universal conventional system. With the exponential development of cloud data and storage room, cloud security has turned out to be one of the intriguing exploration regions of cloud registering servers. Property based encryption is an open key encryption calculation that permits cloud users to anchor their delicate data in the general population cloud servers. Credited based Quantum cryptography will anchor the user data transmission and correspondence through cloud frame programmers. Be that as it may, daze quantum registering will anchor the moment spying or getting to of data handling in cloud from any awful cloud provider or outsider. In this paper we proposed an algorithm based on blind quantum computing for to secure the communication between data owner and CSP. And enhanced the hierarchal attribute-based encryption algorithm using BCQ key sharing which provides user data providing and group accessing of cloud data. The experimental results show that the proposed mechanism is efficient than the existing CP-ABE enhancements.

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