Abstract
With the rapid advancement of cloud computing, the use of third-party cloud datacenters for storing and processing (e.g, scaling and cropping) personal and critical images is becoming more common. For storage and bandwidth efficiency, the images are almost always compressed. Although cloud-based imaging has many advantages, security and privacy remain major issues. One way to address these two issues is to use Shamir’s (k, n) secret sharing-based secret image sharing schemes, which can distribute the secret image among n number of participants in such a way that no less than k (where k ≤ n) participants can know the image content. Existing secret image sharing schemes do not allow processing of a compressed image in the hidden domain. In this paper, we propose a scheme that can scale and crop a CDF (Cohen Daubechies Feauveau) wavelet-based compressed image (such as JPEG2000) in the encrypted domain by smartly applying secret sharing on the wavelet coefficients. Results and analyses show that our scheme is highly secure and has acceptable computational and data overheads.
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Kansal, K., Mohanty, M., Atrey, P.K. (2015). Scaling and Cropping of Wavelet-Based Compressed Images in Hidden Domain. In: He, X., Luo, S., Tao, D., Xu, C., Yang, J., Hasan, M.A. (eds) MultiMedia Modeling. MMM 2015. Lecture Notes in Computer Science, vol 8935. Springer, Cham. https://doi.org/10.1007/978-3-319-14445-0_37
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DOI: https://doi.org/10.1007/978-3-319-14445-0_37
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-14444-3
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