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Reversible Data Hiding and Coupled Chaotic Logistic Map Using Image Encryption

Authors :
K. Anupama
K. Shanooja
Source :
Transactions on Computational Science and Computational Intelligence ISBN: 9783030494995
Publication Year :
2021
Publisher :
Springer International Publishing, 2021.

Abstract

Data hiding and encryption are the two successful techniques to protect the information in public domain while transmission. Conceal information in a cover image and reconstruction of the same cover image after extracting the hidden information without any alteration is recognized as reversible data hiding (RDH) technology. Reversible data hiding is mainly found application in military and medical field applications. Many such types of schemes are technologically advanced to ensure the security, genuineness, and integrity of the images on transmission through Internet or through any other medium. The cover image used here is a gray image and it is preprocessed for prediction error detection. After the detection of possible prediction error pixels, the position of the predicted error pixel is stored in a binary location map. For prediction error detection the median edge detector (MED) is used. By using information in the binary location map, the error position information is inserted to the encrypted image by most significant bit (MSB) substitution method. Chaotic generator used in this work for encryption process is two chaotic logistic map, which is used to produce pseudo-random binary sequence. The encryption algorithm used here is Coupled Chaotic Logistic Map, to generate pseudo-random binary sequence to encrypt the image pixel by pixel. The secret message is embedded into the prediction error highlighted encrypted image by MSB substitution method. MSB prediction method is used in the decoding phase as it is essential for the successful reconstruction of cover image. The embedded image can be productively extracted and the original cover image can absolutely recovered and its PSNR and SSIM value are infinity and 1.00, respectively. By using the coupled logistic chaotic map, high visual security, better NPCR, UACI, and correlation values are achieved.

Details

ISBN :
978-3-030-49499-5
ISBNs :
9783030494995
Database :
OpenAIRE
Journal :
Transactions on Computational Science and Computational Intelligence ISBN: 9783030494995
Accession number :
edsair.doi...........40647370de2c6b14105a4d768469d2bc
Full Text :
https://doi.org/10.1007/978-3-030-49500-8_15