Watermarking algorithm for authentication and self-recovery of tampered images using DWT

Molina-Garcia, Javier; Reyes-Reyes, Rogelio; Ponomaryov, Volodymyr; Cruz-Ramos, Clara

doi:10.1109/msmw.2016.7538148

Cited by 19 publications

(9 citation statements)

References 10 publications

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“…According to the domain embedded, digital watermark embedding algorithms are divided into timespatial embedding, which is fast and relatively easy to operate but is easy to be erased by geometrical attack, and transform domain embedding [16][17][18][19], which is good at resisting geometrical attack but is fragile facing filtering. Moreover, according to the preknowledge related to data before embedding, we classify the embedding method into preknowledge dependent embedding and preknowledge independent embedding.…”

Section: Digital Watermark Digital Watermark (W) Is a Signalmentioning

confidence: 99%

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A Cloud-User Protocol Based on Ciphertext Watermarking Technology

Liu¹,

Zhang²,

Dong³

2017

Security and Communication Networks

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With the growth of cloud computing technology, more and more Cloud Service Providers (CSPs) begin to provide cloud computing service to users and ask for users' permission of using their data to improve the quality of service (QoS). Since these data are stored in the form of plain text, they bring about users' worry for the risk of privacy leakage. However, the existing watermark embedding and encryption technology is not suitable for protecting the Right to Be Forgotten. Hence, we propose a new Cloud-User protocol as a solution for plain text outsourcing problem. We only allow users and CSPs to embed the ciphertext watermark, which is generated and embedded by Trusted Third Party (TTP), into the ciphertext data for transferring. Then, the receiver decrypts it and obtains the watermarked data in plain text. In the arbitration stage, feature extraction and the identity of user will be used to identify the data. The fixed Hamming distance code can help raise the system's capability for watermarks as much as possible. Extracted watermark can locate the unauthorized distributor and protect the right of honest CSP. The results of experiments demonstrate the security and validity of our protocol.

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Section: Digital Watermark Digital Watermark (W) Is a Signalmentioning

confidence: 99%

“…Homomorphic encryption [18] can translate some operations on plain text into other operations on ciphertext. In our solution, we require that data should be encrypted during transferring and embedding process.…”

Section: Homomorphic Encryption (He)mentioning

confidence: 99%

A Cloud-User Protocol Based on Ciphertext Watermarking Technology

Liu¹,

Zhang²,

Dong³

2017

Security and Communication Networks

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“…Other methods proposed in [14] are as follows: selecting key information from an image by performing discrete wavelet transform (DWT), and taking the coefficients from low frequency (LL sub band) of the DWT level-1 and level-2 as watermark, and work on the block with the size of less small, 2 × 2 pixels, so that they can make better image resolution after the error recovery. There is a drawback in this method, that the use of the watermark sub band LL resulting from the two-level DWT is not efficient, because the information from the LL sub band level-1 is the most representative for the reconstruction error.…”

Section: Introductionmentioning

confidence: 99%

Exploiting Self-Embedding Fragile Watermarking Method for Image Tamper Detection and Recovery

Rakhmawati¹,

Suryani²,

Wirawan³

et al. 2019

IJIES

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The increasingly rapid use of digital images makes data security technology become an important issue to ensure the integrity and ownership of the received image. Watermarking technique is a technique that ensures data security including for checking the authenticity of an image. Current developments, not only can test the authenticity of an image, but also can determine the location of damage while fixing it. The method proposed in this paper is through using the block-based technique of self-embedding fragile watermarking, where the watermark is selected from feature images representing the entire image. Four authentication bits and eight recovery bits are generated in each 2x2 non-overlapping block. Authentication bits are embedded in the three least significant bits (LSBs) of the block itself while recovery bits are embedded in the three LSBs of the corresponding mapped block. Our method is efficient as it only uses simple parity check operations and comparison between average intensities as image tamper detection and use the five most significant bits (MSBs) of 2x2 pixels in average for recovery. The experimental results of the tests on cropped images show that the proposed methods allow image recovery with acceptable visual quality better than some of state-of-the-art schemes.

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“…The methods in References [1][2][3][4] are all based on discrete cosine transforms (DCT). Javier et al [5] introduced a watermark scheme for authentication and self-recovery. Inverse halftoning techniques and median filtering were also used to improve the quality of the recovered image.…”

Section: Introductionmentioning

confidence: 99%

“…Inverse halftoning techniques and median filtering were also used to improve the quality of the recovered image. However, to prevent image tampering attacks, both [4] and [5] take only JPEG compression into account.…”

Section: Introductionmentioning

confidence: 99%

A Fragile Watermark Scheme for Image Recovery Based on Singular Value Decomposition, Edge Detection and Median Filter

Xie

Wang

2019

Applied Sciences

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Many fragile watermark methods have been proposed for image recovery and their performance has been greatly improved. However, jagged edges and confusion still exist in the restored areas and these problems need to be solved to achieve a better visual effect. In this paper, a method for improving recovery quality is proposed that adopts singular value decomposition (SVD) and edge detection for tamper detection and then uses a median filter for image recovery. Variable watermark information can be generated that corresponds to block classifications. With mapping and neighborhood adjustment, the area that has been tampered can be correctly detected. Subsequently, we adopt a filtering operation for the restored image obtained after the inverse watermark embedding process. During the filtering operation, a median filter is used to smooth and remove noise, followed by minimum, maximum and threshold operations to balance the image intensity. Finally, the corresponding pixels of the restored image are replaced with the filtered results. The experimental results of six different tampering attacks conducted on eight test images show that tamper detection method with the edge detection can identify the tampered region correctly but has a higher false alarm rate than other methods. In addition, compared with the other three similar methods previously, using a median filter during image recovery not only improves the visual effect of the restored image but also enhances its quality objectively under most tampering attack conditions.

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Watermarking algorithm for authentication and self-recovery of tampered images using DWT

Cited by 19 publications

References 10 publications

A Cloud-User Protocol Based on Ciphertext Watermarking Technology

A Cloud-User Protocol Based on Ciphertext Watermarking Technology

Exploiting Self-Embedding Fragile Watermarking Method for Image Tamper Detection and Recovery

A Fragile Watermark Scheme for Image Recovery Based on Singular Value Decomposition, Edge Detection and Median Filter

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