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Adaptive Particle Swarm Optimization Data Hiding for High Security Secret Image Sharing

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摘要 The main aim of this work is to improve the security of data hiding forsecret image sharing. The privacy and security of digital information have becomea primary concern nowadays due to the enormous usage of digital technology.The security and the privacy of users’ images are ensured through reversible datahiding techniques. The efficiency of the existing data hiding techniques did notprovide optimum performance with multiple end nodes. These issues are solvedby using Separable Data Hiding and Adaptive Particle Swarm Optimization(SDHAPSO) algorithm to attain optimal performance. Image encryption, dataembedding, data extraction/image recovery are the main phases of the proposedapproach. DFT is generally used to extract the transform coefficient matrix fromthe original image. DFT coefficients are in float format, which assists in transforming the image to integral format using the round function. After obtainingthe encrypted image by data-hider, additional data embedding is formulated intohigh-frequency coefficients. The proposed SDHAPSO is mainly utilized for performance improvement through optimal pixel location selection within the imagefor secret bits concealment. In addition, the secret data embedding capacityenhancement is focused on image visual quality maintenance. Hence, it isobserved from the simulation results that the proposed SDHAPSO techniqueoffers high-level security outcomes with respect to higher PSNR, security level,lesser MSE and higher correlation than existing techniques. Hence, enhancedsensitive information protection is attained, which improves the overall systemperformance.
出处 《Computer Systems Science & Engineering》 SCIE EI 2022年第12期931-946,共16页 计算机系统科学与工程(英文)
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