Reversible Data Hiding in Homomorphic Encrypted Domain by Monitoring Ciphertext Group

Authors(2) :-V. Santhi, M. Abinaya

Since few years, a new problem is trying to combine in a single step, compression, encryption and data hiding. So far, few solutions have been proposed to combine image encryption and compression for example. Nowadays, a new challenge consists to embed data in encrypted images. Since the entropy of encrypted image is maximal, the embedding step, considered like noise, is not possible by using standard data hiding algorithms. A new idea is to apply reversible data hiding algorithms on encrypted images by wishing to remove the embedded data before the image decryption. Recent reversible data hiding methods have been proposed with high capacity, but these methods are not applicable on encrypted images. In this paper we propose an analysis of the local standard deviation of the marked encrypted images in order to remove the embedded data during the decryption step. We have applied our method on various images, and we show and analyze the obtained results.

Authors and Affiliations

V. Santhi
Assistant Professor, Dept. of Computer Applications, Bon Secours College for Women Tamil Nadu, India
M. Abinaya
M.Sc Computer Science, Bon Secours College for Women, Thanjavur, Tamil Nadu, India

Standard Data Hiding, Embedding Images

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Publication Details

Published in : Volume 5 | Issue 1 | January-February 2019
Date of Publication : 2019-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 487-490
Manuscript Number : CSEIT1951102
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

V. Santhi, M. Abinaya, "Reversible Data Hiding in Homomorphic Encrypted Domain by Monitoring Ciphertext Group ", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 1, pp.487-490, January-February-2019. Available at doi : https://doi.org/10.32628/CSEIT1951102
Journal URL : https://res.ijsrcseit.com/CSEIT1951102 Citation Detection and Elimination     |      |          | BibTeX | RIS | CSV

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