Digital image watermarking using deep learning: A survey

Computer Science Review, Год журнала: 2024, Номер 53, С. 100662 - 100662

Опубликована: Авг. 1, 2024

Язык: Английский

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Digital to quantum watermarking: A journey from past to present and into the future

Computer Science Review, Год журнала: 2024, Номер 54, С. 100679 - 100679

Опубликована: Сен. 14, 2024

Язык: Английский

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Digital Watermarking Using Artificial Intelligence: Concept, Techniques, and Future Trends

Security and Privacy, Год журнала: 2025, Номер 8(1)

Опубликована: Янв. 1, 2025

ABSTRACT One of the most widely used tools for information security is digital watermarking. Multimedia content, including text, audio, video, and images, frequently uses it. Utilizing watermarking requires different goals. These goals encompass copyright authentication as well protection. It might be necessary watermark to strong or fragile. Applications requiring must include a fragile watermark. However, protection necessitates For resolving variety intelligence‐related issues, machine learning (ML) deep (DL) are solid options. Although it works watermarking, less effective at more common tasks like regression, classification, prediction. A thorough analysis with popular technologies artificial intelligence (AI), DL, ML presented in this article. summary background information, interesting applications also covered.

Язык: Английский

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Digital Watermarking—A Meta-Survey and Techniques for Fake News Detection

IEEE Access, Год журнала: 2024, Номер 12, С. 36311 - 36345

Опубликована: Янв. 1, 2024

During the past few decades, research on digital media watermarking –initially designed for images with envisioned applications of copyright protection or copy control– has significantly evolved respect to other covers (i.e., video, audio, speech) and many more potential applications, including tamper detection, broadcast monitoring, and, recently, fake news detection. As a result, various surveys have tried summarize certain aspects this field as it grown. This led than 130 survey papers being written at different points in time, describing parts scientific efforts focused watermarking. Considering above, aim paper is twofold. First, we conduct meta-survey based 64 selected works, order most notable field, which allows us "draw map" area. Second, focus providing requirements techniques when applied their recent application: detecting multimedia content. Finally, an outline approach taken within DISSIMILAR (Detection newS SocIal MedIa pLAtfoRms) project detection disinformation presented.

Язык: Английский

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A reversible-zero watermarking scheme for medical images

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Июль 27, 2024

The paper addresses the issue of ensuring authenticity and copyright medical images in telemedicine applications, with a specific emphasis on watermarking methods. While several systems only concentrate identifying tampering images, others also provide capacity to restore tampered regions upon detection. authentication techniques imaging have successfully achieved their goals, previous research underscores notable deficiency: resilience these schemes against unintentional attacks has not been sufficiently examined or emphasized research. This indicates need for further development investigation improving robustness image attacks. proposes Reversible-Zero Watermarking approach as solution address problems. new merges advantages both reversible zero techniques. system is comprised two parts. first part zero-watermarking technique that uses VGG19-based feature extraction watermark information establish an ownership share. second incorporates this share into manner using combination discrete wavelet transform, integer difference expansion. Research findings confirm suggested demonstrates substantial enhancements compared current methodologies. indicate NC values are often around 0.9 different attacks, whereas BER close 0. It exceptional qualities being imperceptible, distinguishable, robust. Additionally, provides persistent verification functions independently disputes third-party storage, making it preferred choice domain watermarking.

Язык: Английский

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Robust watermarking against arbitrary scaling and cropping attacks

Signal Processing, Год журнала: 2024, Номер 226, С. 109655 - 109655

Опубликована: Авг. 8, 2024

Язык: Английский

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Reversible Spectral Speech Watermarking with Variable Embedding Locations Against Spectrum-Based Attacks

Applied Sciences, Год журнала: 2025, Номер 15(1), С. 381 - 381

Опубликована: Янв. 3, 2025

To guarantee the reliability and integrity of audio, data have been focused on as an essential topic fast development generative AI. Significant progress in machine learning speech synthesis has increased potential for audio tampering. In this paper, we focus digital watermarking method a promising to safeguard authenticity evidence. Due original with probative importance, algorithm requires reversibility, imperceptibility, reliability. meet requirements, propose reversible approach that embeds feature concentrating high-frequency intDCT coefficients after transforming from time domain into frequency domain. We explored appropriate hiding locations against spectrum-based attacks novel proposed methodologies spectral expansion embedding. However, drawback fixed is stego signal prone being detected by analysis. Therefore, paper proposes two other new embed variable locations—random adaptive distortion estimation embedding—which effectively conceal watermark’s presence while maintaining high perceptual quality average segSNR better than 21.363 dB MOS value 4.085. Our experimental results demonstrate efficacy our both sound preservation log-likelihood value, indicating absolute discontinuity spectrogram embedding evaluate effectiveness algorithm. The result EER indicated performed best

Язык: Английский

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Enhancing Banking Transaction Security with Fractal-Based Image Steganography Using Fibonacci Sequences and Discrete Wavelet Transform

Fractal and Fractional, Год журнала: 2025, Номер 9(2), С. 95 - 95

Опубликована: Фев. 2, 2025

The growing reliance on digital banking and financial transactions has brought significant security challenges, including data breaches unauthorized access. This paper proposes a robust method for enhancing the of transactions. In this context, steganography—hiding information within media—is valuable improving protection. approach combines biometric authentication, using face voice recognition, with image steganography to secure communication channels. A novel application Fibonacci sequences is introduced direct-sequence spread-spectrum (DSSS) system encryption, along discrete wavelet transform (DWT) embedding data. secret message, encrypted through sequences, concealed an tested effectiveness Mean Square Error (MSE) Peak Signal-to-Noise Ratio (PSNR). experimental results demonstrate that proposed achieves high PSNR, particularly grayscale images, robustness measures in mobile online environments.

Язык: Английский

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A Robust Watermarking for Camera‐Captured Images Using Few‐Shot Learning and Simulated Noise Layer

Concurrency and Computation Practice and Experience, Год журнала: 2025, Номер 37(4-5)

Опубликована: Фев. 11, 2025

ABSTRACT With the rise of social media and spread a large number pictures on Internet, protecting data privacy verifying copyright has become hot research. A common method is to use digital watermarking. However, existing blind watermarking methods only consider embedding watermark in image itself ignore fact that attacker can remove through other shooting devices. Therefore, solve this problem, we propose an based few‐shot learning. We autoencoder learn extraction watermarks. Then, framework named Simulated Candid Shooting Layer (SCSL). The SCSL simulates variety candid scenes as noise using meta‐learning enhances robustness Experiments show proposed superior state art technologies both invisibility Specifically, it achieved improvement over 8% evaluation metrics against JPEG attacks. further enhanced these by more than 5%.

Язык: Английский

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Data-free fingerprinting technology for biometric classifiers

Computers & Security, Год журнала: 2025, Номер unknown, С. 104386 - 104386

Опубликована: Март 1, 2025

Язык: Английский

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