Visually meaningful image encryption using data hiding and chaotic compressive sensing

2019 ◽  
Vol 78 (18) ◽  
pp. 25707-25729 ◽  
Author(s):  
R. Ponuma ◽  
R. Amutha ◽  
S. Aparna ◽  
Gayatri Gopal
2017 ◽  
Vol 27 (05) ◽  
pp. 1750073 ◽  
Author(s):  
Jianglin Sun ◽  
Xiaofeng Liao ◽  
Xin Chen ◽  
Shangwei Guo

The increasing need for image communication and storage has created a great necessity for securely transforming and storing images over a network. Whereas traditional image encryption algorithms usually consider the security of the whole plain image, region of interest (ROI) encryption schemes, which are of great importance in practical applications, protect the privacy regions of plain images. Existing ROI encryption schemes usually adopt approximate techniques to detect the privacy region and measure the quality of encrypted images; however, their performance is usually inconsistent with a human visual system (HVS) and is sensitive to statistical attacks. In this paper, we propose a novel privacy-aware ROI image encryption (PRIE) scheme based on logistical mapping and data hiding. The proposed scheme utilizes salient object detection to automatically, adaptively and accurately detect the privacy region of a given plain image. After private pixels have been encrypted using chaotic cryptography, the significant bits are embedded into the nonprivacy region of the plain image using data hiding. Extensive experiments are conducted to illustrate the consistency between our automatic ROI detection and HVS. Our experimental results also demonstrate that the proposed scheme exhibits satisfactory security performance.


2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Ming Li ◽  
Haiju Fan ◽  
Hua Ren ◽  
Dandan Lu ◽  
Di Xiao ◽  
...  

A novel method of meaningful image encryption is proposed in this paper. A secret image is encrypted into another meaningful image using the algorithm of reversible data hiding (RDH). High covertness can be ensured during the communication, and the possibility of being attacked of the secret image would be reduced to a very low level. The key innovation of the proposed method is that RDH is applied to compressive sensing (CS) domain, which brings a variety of benefits in terms of image sampling, communication and security. The secret image after preliminary encryption is embedded into the sparse representation coefficients of the host image with the help of the dictionary. The embedding rate could reach 2 bpp, which is significantly higher than those of other state-of-art schemes. In addition, the computational complexity of receiver is reduced. Simulations verify our proposal.


K Means Clustering (KM) based data hiding algorithm (KM-DH) is to perform cluster operation which means split pixels into chunks from already encrypted image. Under Consideration of splitted pixels find place to allocate information Authenticated person encrypt the image pixels with their key to prepare envelope image then flow goes by grouping the pixels to stuff the already encrypted image of lowest bits to generate place to allocate data using K means Clustering methods with the help of secret key it form split up matrix.In Receiver side after getting the encrypted data they can withdraw data and image separately without overlapping each other using data and image encryption key.At the same time receiver can also get both the image and data without any bug by dimensional link.


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