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Hash-based image watermarking technique for tamper detection and localization

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Abstract

The accumulating and proliferating of the internet has increased ten folds from the year 2010 to 2020 according to the Ericsson report [58]. This trend is further increasing, making the transmission of multimedia much easier. However, the impetuous growth of data breaches and manipulations in multimedia has become a matter of concern. In such a scenario the main concern is the security of multimedia data besides protecting its integrity and authenticity. In this work, a new approach utilizing hashing and watermarking has been proposed for tamper detection and localization of digital images. At first, the original cover image is segmented into 4 × 4 non-overlapping blocks. For each 4 × 4 block, Discrete Cosine Transform (DCT) is applied to extract the DC coefficients. Further, a hash is generated from these coefficients using the SHA-256 hash function. The original cover image is Arnold Transformed and then segmented into 4 × 4 blocks to embed the extracted hash (16 bits in each block). Afterward, Inverse Arnold Transform is applied to obtain the watermarked image. The proposed approach is found to be resistant to different image processing attacks, copy-paste attacks, and copy-move attacks. Moreover, the average PSNR value of 51.16 dB along with the average SSIM value of 0.9965 has been reported for the presented scheme that is higher compared to already existing schemes. Also, the average FPR value for random tampering is found to be 4.6986 that is better compared to the state-of-the-art technique. The scheme can detect and localize the tamper more efficiently compared to the existing schemes making it a competent contender for the said purpose.

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Authors and Affiliations

  1. Department of Electronics and Instrumentation Technology, University of Kashmir, Srinagar, India

    Muzamil Hussan, Shabir A. Parah & Aiman Jan

  2. Department of Higher Education, UT of JK, Srinagar, India

    G. J. Qureshi

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  1. Muzamil Hussan
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  2. Shabir A. Parah
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  3. Aiman Jan
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  4. G. J. Qureshi
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Correspondence to Shabir A. Parah.

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Hussan, M., Parah, S.A., Jan, A. et al. Hash-based image watermarking technique for tamper detection and localization. Health Technol. 12, 385–400 (2022). https://doi.org/10.1007/s12553-021-00632-9

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