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Proceedings Paper

Visual cryptography based robust copyright protection scheme to secure online social networking content with multiple owners

Paper Abstract

Most of the existing visual cryptography (VC) based watermarking schemes consider images of a single owner, however, some real-life applications demand images with multiple owners. In these schemes, pixel expansion, meaningless shares, use of codebook and low robustness against certain attacks are some other challenges. To overcome such challenges, a robust and secure copyright protection scheme for color images is proposed. This scheme uses VC, transform domain and chaos technique. VC ensures the security of the scheme while other techniques are applied to enhance the robustness of the scheme. Transform domain techniques are applied to the R, G and B components of the image to extract its features. These features are used to create the master share. This master share along with the respective watermarks are used to construct the key shares for every owner. The key shares should be some meaningful images and not random looking, so that they do not create any suspicion for some secret information being shared. Hence the constructed key shares are hidden in meaningful cover images using Kukreja et al. scheme. To prove the copyright of the image, the key share stored with the owner is superimposed with the master share to retrieve the watermark. The novelty of the scheme is that it can protect the image having multiple owners by using multiple watermarks, still the original image remains unmodified, as the watermark is not embedded inside it but is hidden in the key shares. The experimental results can prove that the proposed scheme has strong robustness against different image processing attacks, perfect imperceptibility and also satisfy blindness and security properties. Comparisons with the existing schemes show the effectiveness of the proposed scheme.

Paper Details

Date Published: 10 September 2019
PDF: 11 pages
Proc. SPIE 11137, Applications of Digital Image Processing XLII, 111371M (10 September 2019); doi: 10.1117/12.2529387
Show Author Affiliations
Sonal Kukreja, Thapar Institute of Engineering and Technology (India)
Geeta Kasana, Thapar Institute of Engineering and Technology (India)
Singara Singh Kasana, Thapar Institute of Engineering and Technology (India)

Published in SPIE Proceedings Vol. 11137:
Applications of Digital Image Processing XLII
Andrew G. Tescher; Touradj Ebrahimi, Editor(s)

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