Search Results (15)

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

The advancement of artificial intelligence (AI) technologies, including generative pre-trained transformers (GPTs) and generative models for text, image, audio, and video creation, has revolutionized content generation, creating unprecedented opportunities and critical challenges. This paper systematically examines the characteristics, methodologies, and challenges associated with detecting the synthetic content across multiple modalities, to safeguard digital authenticity and integrity. Key detection approaches reviewed include stylometric analysis, watermarking, pixel prediction techniques, dual-stream networks, machine learning models, blockchain, and hybrid approaches, highlighting their strengths and limitations, as well as their detection accuracy, independent accuracy of 80% for stylometric analysis and up to 92% using multiple modalities in hybrid approaches. The effectiveness of these techniques is explored in diverse contexts, from identifying deepfakes and synthetic media to detecting AI-generated scientific texts. Ethical concerns, such as privacy violations, algorithmic bias, false positives, and overreliance on automated systems, are also critically discussed. Furthermore, the paper addresses legal and regulatory frameworks, including intellectual property challenges and emerging legislation, emphasizing the need for robust governance to mitigate misuse. Real-world examples of detection systems are analyzed to provide practical insights into implementation challenges. Future directions include developing generalizable and adaptive detection models, hybrid approaches, fostering collaboration between stakeholders, and integrating ethical safeguards. By presenting a comprehensive overview of AIGC detection, this paper aims to inform stakeholders, researchers, policymakers, and practitioners on addressing the dual-edged implications of AI-driven content creation. Full article

Recently, deep learning has been gradually applied to digital watermarking, which avoids the trouble of hand-designing robust transforms in traditional algorithms. However, most of the existing deep watermarking algorithms use encoder–decoder architecture, which is redundant. This paper proposes a novel audio watermarking algorithm based on adversarial perturbation, AAW. It adds tiny, imperceptible perturbations to the host audio and extracts the watermark with a pre-trained decoder. Moreover, the AAW algorithm also uses an attack simulation layer and a whitening layer to improve performance. The AAW algorithm contains only a differentiable decoder, so it reduces the redundancy. The experimental results also demonstrate that the proposed algorithm is effective and performs better than existing audio watermarking algorithms. Full article

This paper aims to explore an alternative reversible digital watermarking solution to guarantee the integrity of and detect tampering with data of probative importance. Since the payload for verification is embedded in the contents, algorithms for reversible embedding and extraction, imperceptibility, payload capacity, and computational time are issues to evaluate. Thus, we propose a reversible and imperceptible audio information-hiding algorithm based on modified integer discrete cosine transform (intDCT) coefficient expansion. In this work, the original signal is segmented into fixed-length frames, and then intDCT is applied to each frame to transform signals from the time domain into integer DCT coefficients. Expansion is applied to DCT coefficients at a higher frequency to reserve hiding capacity. Objective evaluation of speech quality is conducted using listening quality objective mean opinion (MOS-LQO) and the segmental signal-to-noise ratio (segSNR). The audio quality of different frame lengths and capacities is evaluated. Averages of 4.41 for MOS-LQO and 23.314 [dB] for segSNR for 112 ITU-T test signals were obtained with a capacity of 8000 bps, which assured imperceptibility with the sufficient capacity of the proposed method. This shows comparable audio quality to conventional work based on Linear Predictive Coding (LPC) regarding MOS-LQO. However, all segSNR scores of the proposed method have comparable or better performance in the time domain. Additionally, comparing histograms of the normalized maximum absolute value of stego data shows a lower possibility of overflow than the LPC method. A computational cost, including hiding and transforming, is an average of 4.884 s to process a 10 s audio clip. Blind tampering detection without the original data is achieved by the proposed embedding and extraction method. Full article

Digital multimedia elements such as text, image, audio, and video can be easily manipulated because of the rapid rise of multimedia technology, making data protection a prime concern. Hence, copyright protection, content authentication, and integrity verification are today’s new challenging issues. To address these issues, digital image watermarking techniques have been proposed by several researchers. Image watermarking can be conducted through several transformations, such as discrete wavelet transform (DWT), singular value decomposition (SVD), orthogonal matrix Q and upper triangular matrix R (QR) decomposition, and non-subsampled contourlet transform (NSCT). However, a single transformation cannot simultaneously satisfy all the design requirements of image watermarking, which makes a platform to design a hybrid invisible image watermarking technique in this work. The proposed work combines four-level (4L) DWT and two-level (2L) SVD. The Arnold map initially encrypts the watermark image, and 2L SVD is applied to it to extract the s components of the watermark image. A 4L DWT is applied to the host image to extract the LL sub-band, and then 2L SVD is applied to extract s components that are embedded into the host image to generate the watermarked image. The dynamic-sized watermark maintains a balanced visual impact and non-blind watermarking preserves the quality and integrity of the host image. We have evaluated the performance after applying several intentional and unintentional attacks and found high imperceptibility and improved robustness with enhanced security to the system than existing state-of-the-art methods. Full article

Watermarking is a viable approach for safeguarding the proprietary rights of digital media. This study introduces an innovative fast Fourier transform (FFT)-based phase modulation (PM) scheme that facilitates efficient and effective blind audio watermarking at a remarkable rate of 508.85 numeric values per second while still retaining the original quality. Such a payload capacity makes it possible to embed a full-color image of 64 × 64 pixels within an audio signal of just 24.15 s. To bolster the security of watermark images, we have also implemented the Arnold transform in conjunction with chaotic encryption. Our comprehensive analysis and evaluation confirm that the proposed FFT–PM scheme exhibits exceptional imperceptibility, rendering the hidden watermark virtually undetectable. Additionally, the FFT–PM scheme shows impressive robustness against common signal-processing attacks. To further enhance the visual rendition of the recovered color watermarks, we propose using residual neural networks to perform image denoising and super-resolution reconstruction after retrieving the watermarks. The utilization of the residual networks contributes to noticeable improvements in perceptual quality, resulting in higher levels of zero-normalized cross-correlation in cases where the watermarks are severely damaged. Full article

Digital face approaches possess currently received awesome attention because of their huge wide variety of digital audio, and visual programs. Digitized snapshots are progressively more communicated using an un-relaxed medium together with cyberspace. Consequently, defence, clinical, medical, and exceptional supervised photographs are essentially blanketed towards trying to employ it; such controls ought to damage such choices constructed totally based on those pictures. So, to shield the originality of digital audio/visual snapshots, several approaches proposed. Such techniques incorporate traditional encoding, breakable and nominal breakable watermarking with virtual impressions which are based upon the material of image content. Over the last few decades, various holistic approaches are proposed for improving image identification and verification. In this paper, a combination of both the feature level and score level of different techniques were used. Image is one of the identities of a person which reflects its emotions, feeling, age etc. which also helps to gather an information about a person without knowing their name, caste, and age and this could be not of much importance when it is used for domestic or framing applications. To secure the originality of digital audio/visual impressions many methods come into pictures and are proposed which include digital signatures, watermarking, cryptography, and fragile depend upon face contents. The objective of this research article is to identify & verify real-time video images using feature and score levels using watermarking that will help to judge the authenticity of any images at the initial stage by extracting the features which are evaluated by following an algorithm known as Viterbi and where input data is changed initially into an embedded treat or state then the matrix is evaluated of achieved transformation and on this basis preliminary score estimation will be generated after many iterations for each image that will help in validation. Finally, the tested image will be verified using several approaches to protect and provide security to the original image being verified. This approach may be useful for different surveillance applications for real-time image identification and verification. Also, measurement of accuracy was done by reconfiguring the HMM to identify the constant segmentation and feature removal of the image was settled by initializing parameters and teaching the image feature using the algorithm “Viterbi”. Full article

Digital audio watermarking is a promising technology for copyright protection, yet its low embedding capacity remains a challenge for widespread applications. In this paper, the spread-spectrum watermarking algorithm is viewed as a communication channel, and the embedding capacity is analyzed and modeled with information theory. Following this embedding capacity model, we propose the extended-codebook spread-spectrum (ECSS) watermarking algorithm to heighten the embedding capacity. In addition, the diversity reception (DR) mechanism is adopted to optimize the proposed algorithm to obtain both high embedding capacity and strong robustness while the imperceptibility is guaranteed. We experimentally verify the effectiveness of the ECSS algorithm and the DR mechanism, evaluate the performance of the proposed algorithm against common signal processing attacks, and compare the performance with existing high-capacity algorithms. The experiments demonstrate that the proposed algorithm achieves a high embedding capacity with applicable imperceptibility and robustness. Full article

Multimedia security has received much attention recently because of the rapid transmission of elements such as text, images, audio, video, software, animation and games. Security is becoming especially critical for content owners concerned about the illegal usage of their original products. Encryption and watermarking are two methodologies for digital applications. Spatial domain and frequency domain watermarking algorithms give very promising results in embedding binary images into the cover images. This paper proposed a new method of semi-blind watermarking technique. The digital images are divided into 4 × 4 blocks and converted into discrete Wavelet transformations (DWTs). The binary image is embedded into each block using the flexible scaling factor method. Experimental results show that the proposed method has higher peak signal to noise ratio (PSNR) and similarity ratio (SR) values compared to the standard Wavelet transformation and block-based Wavelet algorithms. The results prove that the proposed hybrid algorithm is more effective, robust, secure and resistant than DWT and block-based DWT algorithms. Full article

Although the development of watermarking techniques has enabled designers to tackle normal processing attacks (e.g., amplitude scaling, noise addition, re-compression), robustness against malicious attacks remains a challenge. The discordant size content replacement attack is an attack against watermarking schemes which performs content replacement that increases or reduces the number of samples in the signal. This attack modifies the content and length of the signal, as well as desynchronizes the position of the watermark and its removal. In this paper, a source-channel coding approach for protecting an audio signal against this attack was applied. Before applying the source-channel encoding, a decimation technique was performed to reduce by one-half the number of samples in the original signal. This technique allowed compressing at a bit rate of 64 kbps and obtaining a watermarked audio signal with an excellent quality scale. In the watermark restoration, an interpolation was applied after the source-channel decoding to recover the content and the length. The procedure of decimation–interpolation was taken because it is a linear and time-invariant operation and is useful in digital audio. A synchronization strategy was designed to detect the positions where the number of samples in the signal was increased or reduced. The restoration ability of the proposed scheme was tested with a mathematical model of the discordant size content replacement attack. The attack model confirmed that it is necessary to design a synchronizing strategy to correctly extract the watermark and to recover the tampered signal. Experimental results show that the scheme has better restoration ability than state-of-the-art schemes. The scheme was able to restore a tampered area of around 20% with very good quality, and up to $58.3$% with acceptable quality. The robustness against the discordant size content replacement attack was achieved with a transparency threshold above $-2$. Full article

Zero watermarking does not alter the original information contained in vector map data and provides perfect imperceptibility. The use of zero watermarking for data copyright protection has become a significant trend in digital watermarking research. However, zero watermarking encounters tremendous obstacles to its development and application because of its requirement to store copyright information with a third party and its difficulty in confirming copyright ownership. Aiming at the shortcomings of the existing zero watermarking technology, this paper proposes a new zero watermarking construction method based on the angular features of vector data that store the zero watermarking and copyright information on the blockchain after an XOR operation. When the watermark is being extracted, the copyright information can be extracted with the XOR operation to obtain the information stored on the blockchain. Experimental results show that the combination of zero watermarking and blockchain proposed in this paper gives full play to the advantages of the two technologies and protects the copyright of data in a lossless fashion. Compared with the traditional zero watermarking algorithms, the proposed zero watermarking algorithm exhibits stronger robustness. Moreover, the proposed data copyright protection framework with a combination of zero watermarking and blockchain can also be applied to other data types, such as images, audio, video, and remote sensing images. Full article

We develop in this paper a method for constructing a digital watermark to protect one-dimensional and two-dimensional signals. The creation of a digital watermark is based on the one-dimensional and two-dimensional generalized Fourier and Hartley transformations and the Ateb-functions as a generalization of trigonometric functions. The embedding of the digital watermark is realized in the frequency domain. The simulation of attacks on protected files is carried out to confirm the stability of the proposed method. Experiments proved the high stability of the developed method conformably to the main types of attacks. An additional built-in digital watermark can be used to identify protected files. The proposed method can be used to support the security of a variety of signals—audio, images, electronic files etc.—to protect them from unauthorized access and as well for identification. Full article

Digital watermarking has been widely utilized for ownership protection of multimedia contents. This paper introduces a blind symmetric audio watermarking algorithm based on parametric Slant-Hadamard transform (PSHT) and Hessenberg decomposition (HD). In our proposed algorithm, at first watermark image is preprocessed to enhance the security. Then, host signal is divided into non-overlapping frames and the samples of each frame are reshaped into a square matrix. Next, PSHT is performed on each square matrix individually and a part of this transformed matrix of size m×m is selected and HD is applied to it. Euclidean normalization is calculated from the 1st column of the Hessenberg matrix, which is further used for embedding and extracting the watermark. Simulation results ensure the imperceptibility of the proposed method for watermarked audios. Moreover, it is demonstrated that the proposed algorithm is highly robust against numerous attacks. Furthermore, comparative analysis substantiates its superiority among other state-of-the-art methods. Full article

High Efficiency Advanced Audio Coding (HE-AAC) is a lossy compression method for digital audio data which supplies high-quality audio at a very low bit rate. In this paper, the audio blind watermarking algorithm, on the basis of autocorrelation modulation, is introduced to maximize the robustness against low-bit rate HE-AAC. The watermark is embedded by modulating the normalized correlation of the original signal as well as its delayed version. The signal-to-noise ratio of before and after HE-AAC compression decides the strength of the embedding watermark. The watermarking embedding strength is guaranteed by the feedback process. The effectiveness of the proposed method is proven using the Perceptual Evaluation of Audio Quality algorithm and bit error rate of recovered watermarks under HE-AAC compression on mono, stereo and 5.1 channel audio. Experimental results show that the proposed method provides good performance in terms of imperceptibility, robustness and data payload compared with some recent state-of-the-art watermarking methods under an MPEG-2 Audio Layer III (MP3) compression attack. Full article

An adaptive and blind audio watermarking algorithm is proposed based on chaotic encryption in discrete cosine transform (DCT) and discrete wavelet transform (DWT) hybrid domain. Since human ears are not sensitive to small changes in the high-frequency components of the audio media, the encrypted watermark can be embedded into the audio signal according to the special embedding rules. The embedding depth of each audio segment is controlled by the overall average amplitude to effectively improve the robustness and imperceptibility. The watermark is encrypted by a chaotic sequence to improve the security of watermark, so only users who hold the correct key can accurately extract the watermark without the original audio signal. Experimental results show that the proposed algorithm has larger capacity, higher imperceptibility, better security, and stronger robustness when combating against signal-processing attacks than the involved audio watermarking algorithms in recent years. Full article