Research Output

A Secure and Robust Image Hashing Scheme Using Gaussian Pyramids

  Image hash is an alternative to cryptographic hash functions for checking integrity of digital images. Compared to cryptographic hash functions, an image hash or a Perceptual Hash Function (PHF) is resilient to content preserving distortions and sensitive to malicious tampering. In this paper, a robust and secure image hashing technique using a Gaussian pyramid is proposed. A Gaussian pyramid decomposes an image into different resolution levels which can be utilized to obtain robust and compact hash features. These stable features have been utilized in the proposed work to construct a secure and robust image hash. The proposed scheme uses Laplacian of Gaussian (LOG) and disk filters to filter the low-resolution Gaussian decomposed image. The filtered images are then subtracted and their difference is used as a hash. To make the hash secure, a key is introduced before feature extraction, thus making the entire feature space random. The proposed hashing scheme has been evaluated through a number of experiments involving cases of non-malicious distortions and malicious tampering. Experimental results reveal that the proposed hashing scheme is robust against non-malicious distortions and is sensitive to detect minute malicious tampering. Moreover, False Positive Probability (FPP) and False Negative Probability (FNP) results demonstrate the effectiveness of the proposed scheme when compared to state-of-the-art image hashing algorithms proposed in the literature.

  • Type:

    Article

  • Date:

    19 November 2019

  • Publication Status:

    Published

  • Publisher

    MDPI AG

  • DOI:

    10.3390/e21111132

  • Cross Ref:

    e21111132

  • Funders:

    Historic Funder (pre-Worktribe)

Citation

Bashir, I., Ahmed, F., Ahmad, J., Boulila, W., & Alharbi, N. (2019). A Secure and Robust Image Hashing Scheme Using Gaussian Pyramids. Entropy, 21(11), https://doi.org/10.3390/e21111132

Authors

Keywords

hash; digital image; security; distortions; False Positive Probability (FPP); False Negative Probability (FNP)

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