Iterative compensation schemes for multimedia content authentication

Ababneh, S.; Ansari, Rashid; Khokhar, Ashfaq

doi:10.1016/j.jvcir.2009.03.010

Cited by 15 publications

(4 citation statements)

References 16 publications

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“…In this approach, the digital signature retrieved from an image is compared with the digital signature stored by the third party. Comparing the two signatures helps us to detect whether the image has been tampered with or not [5,6,7,8]. The watermarking method can be categorized into robust watermarking [9,10,11,12,13,14,15], semi-fragile watermarking [16,17,18,19] and fragile watermarking [20,21,22,23,24,25,26,27,28,29,30,31,32,33,34].…”

Section: Introductionmentioning

confidence: 99%

Self-Embedding Authentication Watermarking with Effective Tampered Location Detection and High-Quality Image Recovery

Lee

Shen

Chen

et al. 2019

Sensors

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Recently, sensor networks have emerged as a high-impact research area, and a number of high profile applications have been proposed. Although significant progress has already been made on securing basic network protocols, additional research is needed to produce techniques and methods for protecting canonical tasks in wireless sensor networks. In this paper, we propose an effective self-embedding authentication watermarking method for tampered location detection and image recovery. The proposed detection method is classified into block-wise and pixel-wise. In block-wise detection, if the size of the block is small, the false positive rate (FPR) will be low. In pixel-wise detection, when the tampered pixels are detected, only the corresponding pixel area is marked. Therefore, the FPR will be lower than that of the block-wise detection. The experimental results demonstrate that the proposed method was effective, and accurate tamper detection and high-quality recovery can be realized even in highly tampered images.

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Section: Introductionmentioning

confidence: 99%

Self-Embedding Authentication Watermarking with Effective Tampered Location Detection and High-Quality Image Recovery

Lee

Shen

Chen

et al. 2019

Sensors

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show abstract

“…In this approach, the digital signature extracted from the image is compared to a digital signature stored by a third party. Comparing the two signatures may detect if the image has been tampered with [3][4][5]. This method makes it easy to determine whether an image is authentic or not, but they cannot find the tampered area.…”

Section: Introductionmentioning

confidence: 99%

Self-Embedding Fragile Watermarking Scheme to Detect Image Tampering Using AMBTC and OPAP Approaches

Kim

Yang

2021

Applied Sciences

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Research on self-embedding watermarks is being actively conducted to solve personal privacy and copyright problems by image attack. In this paper, we propose a self-embedded watermarking technique based on Absolute Moment Block Truncation Coding (AMBTC) for reconstructing tampered images by cropping attacks and forgery. AMBTC is suitable as a recovery bit (watermark) for the tampered image. This is because AMBTC has excellent compression performance and image quality. Moreover, to improve the quality of the marked image, the Optimal Pixel Adjustment Process (OPAP) method is used in the process of hiding AMBTC in the cover image. To find a damaged block in a marked image, the authentication data along with the watermark must be hidden in the block. We employ a checksum for authentication. The watermark is embedded in the pixels of the cover image using 3LSB and 2LSB, and the checksum is hidden in the LSB. Through the recovering procedure, it is possible to recover the original marked image from the tampered marked image. In addition, when the tampering ratio was 45%, the image (Lena) could be recovered at 36 dB. The proposed self-embedding method was verified through an experiment, and the result was the recovered image showed superior perceptual quality compared to the previous methods.

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“…In general, image authentication schemes can be classified into two categories. One is the signature-based approach [1,13] and the other is the fragile watermarking approach [2-7, 12, 16]. In signature-based schemes, a host image is applied to the hash function and the hashed result is then encoded by using a public key cryptosystem to produce the corresponding digital signature.…”

Section: Introductionmentioning

confidence: 99%

Subsampling-Based Image Tamper Detection and Recovery Using Quick Response Code

2015

IJSIA

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Quick response (QR) code is the prevalent trademark for a type of matrix barcode symbol. That code is always scanned to efficiently acquire data, especially for mobile device users. It involves the capabilities of data storage, reliable readability and strong error correction. This paper utilizes these properties of a QR code to propose an image tamper detection and recovery scheme for grayscale images. The image to be protected is first subsampled and decomposed the principal energy compaction for image blocks. These are regarded as the image authentication and recovery data and then are encoded into the pattern of a QR code. The QR code is subsequently embedded into the original image. Experimental results showed that the authentication and recovery data in a QR code is able to sustain certain perceptible distortions such that the proposed scheme can detect tampered regions clearly and recover them roughly. Moreover, the proposed scheme also provides a better embedded image quality in comparison with the previous method.

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Iterative compensation schemes for multimedia content authentication

Cited by 15 publications

References 16 publications

Self-Embedding Authentication Watermarking with Effective Tampered Location Detection and High-Quality Image Recovery

Self-Embedding Authentication Watermarking with Effective Tampered Location Detection and High-Quality Image Recovery

Self-Embedding Fragile Watermarking Scheme to Detect Image Tampering Using AMBTC and OPAP Approaches

Subsampling-Based Image Tamper Detection and Recovery Using Quick Response Code

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