Secure transmission of data using audio watermarking with protection on synchronization attack

This paper presents an audio watermarking scheme that ensures the efficient of robustness-distortion ratio and a pleasing amount of capacity. Quantization Index Modulation (QIM) method synergism along with Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT), Singular Value Decomposition (SVD), and Cartesian to Polar Transformation (CPT) to emphasize copyright protection for harmonical work of art. DWT synergism along with DCT, SVD, and CPT to emphasize copyright protection for harmonical work of art. The system establishes with DWT that divides the signal within a specific range of frequency, alter it to the frequency domain by DCT, partite with mathematical processing SVD, and transform the peculiar value of matrix-S to polar value using CPT, furthermore, QIM embed the watermark into the angular value from the CPT. The system performance is astonishing, tested using 4 different audio host signal and evaluated considers to desirable Bit Error Rate (BER) <; 0.025, Signal-to-Noise Ratio (SNR)>21dB, a great amount of data payload that is 525 bit per second, and the noise caused by watermark is inaudible. All of the experiments, trials, and results show that the designed audio watermarking system is robust and imperceptible.

Many effective watermarking algorithms have been proposed and implemented for digital images and digital video. However, a few algorithms have been proposed for audio watermarking. This is due to the fact that, human auditory system (HAS) is far more complex and sensitive than human visual system (HVS). In this research work, a new method of embedding image data into the audio signal and additive audio watermarking algorithm based on Discrete Cosine Transformation (DCT) domain is proposed. First, the original audio is transformed into DCT domain. The DCT coefficients are divided into a fixed number of subsections and the energy of each subsection is calculated. Next, watermark is generated from image by image processing algorithm. Watermarks are then embedded into selected peaks of highest energy subsection. Experimental results demonstrate that the watermark is inaudible and this algorithm is robust to common operations of digital audio signal processing, such as noise addition, re-sampling, requantization and so on. To evaluate the performance of the proposed audio watermarking method, subjective and objective quality tests including Bit Error Rate (BER) and Signal to Noise ratio (SNR) are conducted.

Rapid development of the digital technology and internet has made copyright protection and ownership verification of digital audio data hot research topics that have attracted a lot of interest from different parties. Since the traditional audio protection algorithms cannot solve all the problems of audio copyright protection and digital right management (DRM) due to the unique audio data features and algorithm limitations, this thesis is proposed to address the issue of audio copyright protection using watermarking techniques. Firstly, a new perception-based watermarking scheme for MPEG-4 scalable to lossless (SLS) audio is proposed. Under the control of the psychoacoustic model, the significant part of integer modified discrete cosine transform (IntMDCT) coefficients are adaptively modified during MPEG-4 SLS audio compression taking robustness, imperceptibility and security into consideration. The chaotic watermark generated by chaos is then embedded to ensure security. Moreover, the adaptive spread spectrum (SS) method is exploited to further optimize the tradeoff between robustness and transparency of this scheme. Secondly, a blind and robust audio watermarking scheme based on singular value decomposition (SVD) – followed by discrete cosine transform (DCT) with the synchronization code technique is proposed. A binary watermark is embedded into the high frequency band of the SVD-DCT block. Chaotic sequence is adopted as the synchronization code and inserted into the host signal. Thirdly, a new and robust audio watermarking scheme based on lifting wavelet transform (LWT) and SVD is proposed. Specifically, the watermark data is efficiently inserted in the low coefficient of the frequency subband of LWT audio taking advantage of both SVD and quantization index modulation (QIM). Furthermore, the synchronization code technique is also integrated in the hybrid LWT-SVD audio watermarking method. Finally, a particle swarm optimization (PSO) and SVD based audio watermarking scheme is proposed. The watermark is embedded by modifying singular values (SVs) of the host audio signal with the SS method. The designed optimization technique employs PSO to search for the optimal watermark strength by continuously adjusting the fitness values so that the conflicting requirements of robustness and imperceptibility of the watermark are satisfied optimally. Moreover, the proposed scheme has the flexibility to include or remove various watermarking attacks during training for optimization. The experimental results validate the practicality of the proposed methods and show that the proposed algorithms are very robust to typical signal manipulations. Furthermore, the results of comparison with other similar state-of-the-art audio watermarking techniques indicate that the proposed algorithms are more robust against most common signal processing attacks while preserving good imperceptibility.

This paper presents a new robust hybrid multiple watermarking technique using fusion of discrete wavelet transforms (DWT), discrete cosine transforms (DCT), and singular value decomposition (SVD) instead of applying DWT, DCT and SVD individually or combination of DWT-SVD / DCT-SVD. For identity authentication purposes, multiple watermarks are embedded into the same medical image / multimedia objects simultaneously, which provides extra level of security with acceptable performance in terms of robustness and imperceptibility. In the embedding process, the cover image is decomposed into first level discrete wavelet transforms where the A (approximation/lower frequency sub-band) is transformed by DCT and SVD. The watermark image is also transformed by DWT, DCT and SVD. The S vector of watermark information is embedded in the S component of the cover image. The watermarked image is generated by inverse SVD on modified S vector and original U, V vectors followed by inverse DCT and inverse DWT. The watermark is extracted using an extraction algorithm. Furthermore, the text watermark is embedding at the second level of the D (diagonal sub-band) of the cover image. The security of the text watermark considered as EPR (Electronic Patient Record) data is enhanced by using encryption method before embedding into the cover. The results are obtained by varying the gain factor, size of the text watermark, and cover medical images. The method has been extensively tested and analyzed against known attacks and is found to be giving superior performance for robustness, capacity and reduced storage and bandwidth requirements compared to reported techniques suggested by other authors.

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.

Audio watermarking is a data hiding technology widely used to increase the authentication of audio files and for copyright protection. Watermarking techniques hides copyright information, which can be a binary sequence or an image, within the audio signal in such a way that it is not perceivable by the listener. A large number of audio watermarking techniques are available. Authentication requires only a simple watermarking technique but to ensure security along with authentication, strong watermarking methods should be adopted. The proposed method uses watermarking based on Modified Discrete Fourier Transform (MDCT). Experimental analysis shows that the proposed method provides high audio quality when compared to other methods such as Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT).

Audio watermarking is a relatively new technology that aims to embed copyright information in audio signals as a proof of their ownership. The driving force behind this technology has been the ever-increasing illegal manipulation of genuine audio products released by the music industry. In this paper, we propose an effective, robust, and inaudible audio watermarking algorithm. The effectiveness of algorithm has been brought by virtue of applying a cascade of two powerful mathematical transforms; the discrete wavelets transform (DWT) and the singular value decomposition (SVD). Reported experimental results demonstrate the effectiveness of the proposed algorithm.

Telemedicine is well known application where enormous amount of medical data need to be transferred securely over network and manipulate effectively. Security of digital data, especially medical images, becomes important for many reasons such as confidentiality, authentication and integrity. Digital watermarking has emerged as a advanced technology to enhance the security of digital images. The insertion of watermark in medical images can authenticate it and guarantee its integrity. The watermark must be generally hidden does not affect the quality of the medical image. In this paper, we propose blind watermarking based on Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Singular Value Decomposition (SVD), we compare the performance of this technique with watermarking based DWT and SVD. The proposed method DWT, DCT and SVD comparatively better than DWT and SVD method.

An enhanced hybrid image watermarking scheme for security of medical and non-medical images based on DWT and 2-D SVD

Audio watermarking algorithm against synchronization attacks using global characteristics and adaptive frame division

Nowadays image authentication plays a vital role for security. Watermarking techniques facilitate to hide the data in carrier image in such a way so that data would become imperceptible. Watermarking can be performed either in spatial domain or in transfer domain. Least Significant Bit (LSB) modification is the simple but non reliable theme, which is performed in spatial domain. In transfer domain, Singular Value Decomposition (SVD), Discrete Cosine Transformation (DCT), Fast Fourier Transformation (FFT), Discrete Wavelet Transformation (DWT) and Fast hadamard Transform (FHT) etc provide robust result. The goal of the paper is to present how such methods are useful to authenticate images and avoid image tampering. In our work, we have discussed block and non block based watermarking scheme performed in DCT domain using SVD. Several experiments are carried out to check the robustness of the algorithm. We conclude that non block based algorithm is superior in terms of visual quality after embedding and extraction, while its inferior in terms of some common signal processing attacks like rotation, scaling, translation etc.

Audio watermarking is a method that embeds inaudible information into digital audio data. This paper proposes an audio watermarking technique for protecting audio copyrights based on human psychoacoustic model (HPM), discrete wavelet transform (DWT), neural network (NN) and error correcting code. Our technique exploits frequency perceptual masking studied in HPM to guarantee that the embedded watermark is inaudible. To assure watermark embedding and extraction, neural network is used to memorize the relationships between a Wavelet central sample and its neighbors. To increase robustness of the scheme, the watermark is refined by the Hamming error correcting code while the encoded mark is embedded as new watermark in the transformed audio signal. Our audio watermarking algorithm is robust to common audio signal manipulations like MP3 compression, noise addition, silence addition, bit per sample conversion, noise reduction, dynamic changes and Notch filtering. Furthermore, it allows blind retrieval of embedded watermark which does not need the original audio and makes the watermark perceptually inaudible.

The technology of embedding image data into the audio signal and additive audio watermarking algorithm based on SNR to determine a scaling parameter was researched. The audio based on DWT. The intensity of embedded watermarks on the original audio signal is modified by adaptively modulation of the scaling parameter. Experimental result demonstrate that the watermark is inaudible and this algorithm is robust to many operations of digital audio signal processing, such as, resampling, lowpass filter and so on. The extracted watermark image quality is shown by considering normalize correlation (NC) value with a suitable scaling parameter for embedding.

This chapter extensively delves into the realm of digital image watermarking, encompassing comparisons with analogous information security methodologies, elucidations of watermark embedding and extraction procedures, discussions on watermark attributes and applications, overviews of prevalent watermarking tactics, and a concise recapitulation of secure watermarking approaches. The primary focus of this discourse lies in advanced strategies for shielding healthcare data using digital watermarking techniques, with special emphasis on the integration of discrete wavelet transform (DWT), discrete cosine transform (DCT), and singular value decomposition (SVD). Recognizing the inherent challenges in safeguarding medical data amidst the dynamic healthcare landscape, the investigation explores multifaceted watermarking algorithms. Leveraging foundational principles from DWT, DCT, and SVD, the study amalgamates prior research and provides comparative evaluations of the efficacy of these methodologies through tabular representations.

We have proposed a novel audio watermarking technology, which embeds a set of bitstream data by changing two-channel stereo locations of lower frequency components in an embedding target audio signal. This method features nearly lossless embedding, robustness against lossy data compression or analogue conversion, and enables contactless asynchronous detection of embedded watermarks through speaker and microphone devices without the original audio signals. In this paper, we propose an extended monaural audio watermark embedding method, which supports both monaural and stereo audio signals, and enables watermark detection by a single monaural microphone such as cell phone voice receiver devices. We describe an abstract of our proposed watermark embedding and extracting algorithm, and experimental results of watermark extraction precision.