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High Capacity Data Hiding in Encrypted Image Based on Compressive Sensing for Nonequivalent Resources
Authors:Di Xiao  Jia Liang  Qingqing Ma  Yanping Xiang  Yushu Zhang
Affiliation: Department of Technology, Innovation and Computer Science, Long Island University, 1 University Plaza, Brooklyn, NY 11201, USA.
Abstract:To fulfill the requirements of data security in environments with nonequivalent resources, a high capacity data hiding scheme in encrypted image based on compressive sensing (CS) is proposed by fully utilizing the adaptability of CS to nonequivalent resources. The original image is divided into two parts: one part is encrypted with traditional stream cipher; the other part is turned to the prediction error and then encrypted based on CS to vacate room simultaneously. The collected non-image data is firstly encrypted with simple stream cipher. For data security management, the encrypted non-image data is then embedded into the encrypted image, and the scrambling operation is used to further improve security. Finally, the original image and non-image data can be separably recovered and extracted according to the request from the valid users with different access rights. Experimental results demonstrate that the proposed scheme outperforms other data hiding methods based on CS, and is more suitable for nonequivalent resources.
Keywords:Compressive sensing  encrypted image  data hiding  prediction error  nonequivalent resources  
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