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The tampering detection problem can be stated as follows: given an image, detect whether it has been tampered through crop-and-paste and if so, locate the region where the crop-and-paste occurred.
Video tampering detection research requires an inclusive database of video modification.
The experimental results show, that our algorithm achieves high image quality and high tampering detection resolution at a low watermark payload, compared to block-based authentication schemes.
This database has been made publically available for research on splicing, Swapping frames, and copymove tampering, and, as such, various video tampering detection issues with ground truth.
For the purpose of content notation and/or tampering detection, the cloud servers need to embed some additional information directly in these encrypted images.
We leverage RFID tag cooperation to enforce tampering detection.
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In this work, a semi-fragile watermarking scheme, for grayscale image authentication and tamper detection, is proposed.
Cryptographic hardware achieves high-level security such as through encryption processors, random number generators, and tamper detection circuits.
After tamper detection procedure, the next process of the proposed scheme is content reconstruction procedure so as to restore the image block, especially for the suspected tampered blocks.
However, the best watermarking approach, which provides security against communication channel attack, authentication, and tamper detection, is the semi-fragile speech watermarking approach.
Thus, judging the authenticity and integrity of audio data by human perception alone is far from enough, tamper detection is increasingly essential to secure audio applications.
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