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Echo Hiding
Abstract
Homomorphic signal-processing techniques are used to place information imperceivably into audio data streams by the introduction of synthetic resonances in the form of closely-spaced echoes. These echoes can be used to place digital identification tags directly into an audio signal with minimal objectionable degradation of the original signal.
... In the past, many audio watermarking methods have been proposed, e.g. support vector [8,9], phase coding [10], spread spectrum [11,12], techniques based on masking [13,14], patchwork [15,16], echo-hiding [17][18][19][20][21][22][23], and so on. As one typical audio watermarking method, echo-hiding has a simple and easy-tooperate embedding and detection process. ...
... Besides, the watermark detection of echo-hiding does not need the original signal (i.e. it is a blind method). The echo-hiding method was first proposed by Gruhl et al. [17], who described how to embed the watermarks using one backward echo kernel and how to detect it using cepstrum operations. As a critical factor for echo-hiding, echo kernel plays a vital role which greatly affects the performance of the watermarking method. ...
... Therefore, it is impossible to detect the watermarks directly through cepstrum analysis in these watermarking schemes. In order to obtain the watermarks, the corresponding PN sequence must be used for correlation operation after the cepstrum analysis, which greatly increases the security of the basic echo-hiding methods [17,[24][25][26][27]. In [19], the PN sequence-based echo-hiding method was further improved. ...
Echo‐hiding has been widely studied for audio watermarking. This study proposes a more secure echo‐hiding method based on modified pseudo‐noise (PN) sequence and robust principal component analysis (RPCA). In the proposed method, the RPCA is used to decompose the original audio signal into low‐rank and sparse parts and then a pair of opposite modified PN sequences is employed to embed watermarks. The modified PN sequence improves the robustness of watermark detection by providing additional correlation peaks. Meanwhile, benefit from the RPCA and the opposite PN sequences, the security of the proposed method is improved since watermarks cannot be detected from the whole signal even if the PN sequence is known, which is an obvious improvement compared with the previous PN‐based echo‐hiding methods. In the watermark detection process, the authors make use of the low‐rank and sparse characteristics of the watermarked signal to detect watermarks from the low‐rank and sparse parts, respectively. Based on this basic framework, they also propose a multi‐bit embedding scheme, which obtains a doubled embedding capacity compared with the previous PN‐based echo‐hiding methods. The proposed method was evaluated with respect to inaudibility, security, and robustness. The experiment results verified the effectiveness of the proposed method.
... iii) Existing attacks to audio watermarking systems are comprehensively studied and evaluated against a series of representative audio watermarking systems. The attacks include basic signal processing attacks, advanced desynchronization attacks, and the most challenging Digital Audio Watermarking Information Theory [6], [8]- [14] Countermeasures [67]- [70] Time Domain Methods [15]- [35] Transform Domain Methods [7], [36]- [66] Time Aligned [15]- [26] Echo-Based [27]- [35] SS [7], [36]- [52] QIM [53]- [60] Patchwork [36], [61]- [66] Methodology [7], [15]- [66] Replacement Attack [67]- [69] Mask Attack [70] Figure 2: Categorization of existing digital audio watermarking works. ...
... In early 2000's, a new class of embedding methods, termed as quantization index modulation (QIM), was introduced in [53], for general multimedia formats. Other than technique groups incorporated from other research areas, a series of time domain methods have been proposed as unique solutions to deal with audio format, among which the pioneering works are [15] and [27]. ...
... Noticeably, the work in [27] revealed a new paradigm termed as echo-based audio watermarking. ...
Digital audio watermarking is an important technique to secure and authenticate audio media. This paper provides a comprehensive review of the twenty years' research and development works for digital audio watermarking, based on an exhaustive literature survey and careful selections of representative solutions. We generally classify the existing designs into time domain and transform domain methods, and relate all the reviewed works using two generic watermark embedding equations in the two domains. The most important designing criteria, i.e., imperceptibility and robustness, are thoroughly reviewed. For imperceptibility, the existing measurement and control approaches are classified into heuristic and analytical types, followed by intensive analysis and discussions. Then, we investigate the robustness of the existing solutions against a wide range of critical attacks categorized into basic, desynchronization, and replacement attacks, respectively. This reveals current challenges in developing a global solution robust against all the attacks considered in this paper. Some remaining problems as well as research potentials for better system designs are also discussed. In addition, audio watermarking applications in terms of US patents and commercialized solutions are reviewed. This paper serves as a comprehensive tutorial for interested readers to gain a historical, technical, and also commercial view of digital audio watermarking.
... To overcome this problem, it is better to use Gray code which ensures hamming distance among two successive numbers is always 1. PBC provides much better region for secret data embedding in BPCS. But due to Hamming Cliff problem, CGC is preferred over PBC in BPCS [70]. Binary code can be easily converted to gray code by using the following formula: g = g 1 g k 1 is the most significant representation and ⊕ represents XOR operation. ...
... In parity encoding approach, audio signal is broken into number of samples [69]. In echo hiding method, a short echo signal is introduced as part of cover audio where secret message is hidden [70]. The widespread frequency domain techniques are: ...
... To overcome this problem, it is better to use Gray code which ensures hamming distance among two successive numbers is always 1. PBC provides much better region for secret data embedding in BPCS. But due to Hamming Cliff problem, CGC is preferred over PBC in BPCS [70]. Binary code can be easily converted to gray code by using the following formula: g = g 1 g k 1 is the most significant representation and ⊕ represents XOR operation. ...
... In parity encoding approach, audio signal is broken into number of samples [69]. In echo hiding method, a short echo signal is introduced as part of cover audio where secret message is hidden [70]. The widespread frequency domain techniques are: ...
... Namun, tidak dipungkiri ada juga penelitian yang dikembangkan untuk meningkatkan dua hal tersebut. Khususnya untuk penelitian yang terkait dengan media pembawanya, berupa berkas audio, ada berbagai macam metode yang dapat digunakan dalam proses penyisipan data pada berkas audio, antara lain LSB; echo hiding, dilakukan dengan menyisipkan satu bit data rahasia pada sinyal echo [15]; phase coding, yaitu penyisipan dengan mengubah sinyal ke domain frekuensi menggunakan discrate fourier transform (DFT) [16]; spread spectrum, yaitu penyisipan dengan proses modulasi yang diawali dengan proses enkripsi pada pesan rahasia [17]; tone insertion, yang menggunakan tone rendah untuk ruang penyisipan [18]; dan LSD, yaitu hasil sampling sinyal disisipkan berupa nilai desimal [19]. ...
Nowadays, the needs of data security is proportional to the amount of data usage as the effect from easiness in internet access. There are many ways to protect data in order to avoid data leakage, such as cryptography, watermarking, and data hiding. The latter is conducted by hiding secret data into a carrier. A popular method in data hiding is Least significant digit (LSD). The hiding is carried out by changing the value of binary secret data into decimal in specific segment. Then, the decimal value of secret data is inserted into the carrier. The process in LSD method is relatively simple and easier to implement, but the LSD has weakness in pivoting point as reference of data changes. This results in a change into the original data carrier. Additionally, this also has limited amount of data capacity that can be inserted.
On the other hand, Global-Section Search method (GSS) is an optimization method used to find an optimum value between two signals. Newly acquired signal GSS is further used as a pivoting point and slot area to paste the data secret.
This study proposes a new method of data hiding by using Least Significant Digit and Global-section search (LSD-GSS) to increase the capacity of secret data insertion. The performance of LSD-GSS as proposed method is tested by comparing the LSD method and using 15 data sets of audio in various genres as carrier media and various large capacity of 12 secret data. SNR is used to find out the quality of hidden data audio. The experimental result shows that the LSD-GSS has increased the capacity of secret data that can be inserted without changing the original data carrier.
... Also, humans have a limitation to high frequency domain and low frequency domain (Cox, Miller, & Muttoo, 2002). There are many researches for audio watermark and many of them use a psychoacoustic model for implementations (Baumgarte, Ferekidis, & Fuchs, 1995;Boney, Tewfik, & Hamdy, 1996;Gruhl, Lu, & Bender, 1996;Wolfe & Godsill, 2000). ...
In this chapter, we propose a new information hiding and extracting method without embedding any information into the target content by using a nonlinear feature extraction scheme trained on frequency domain. The proposed method can detect hidden bit patterns from the content by processing the coefficients of the selected feature subblocks to the trained neural network. The coefficients are taken from the frequency domain of the decomposed target content by frequency transform. The bit patterns are retrieved from the network only with the proper extraction keys provided. The extraction keys, in the proposed method, are the coordinates of the selected feature subblocks and the neural network weights generated by the supervised learning of the neural network. The supervised learning uses the coefficients of the selected feature subblocks as the set of input values, and the hidden bit patterns are used as the teacher signal values of the neural network, which is the watermark signal in the proposed method. With our proposed method, we are able to introduce a watermark scheme with no damage to the target content.
Watermarking is the process of embedding information into a host signal, and it’s a significant process when it enters into the copyright protection or digital works. In the near future, quantum computing will be developed and therefore the protection of quantum data will be a vital issue. This paper proposes a novel quantum reversible realization of echo hiding-based audio watermarking in the quantum representation of digital signal (QRDS). In the embedding process, according to watermark qubits, some echo frames are generated by modifying time and amplitude qubits of host audio frames. Then, a watermarked quantum audio signal is obtained; as a sum on quantum host and quantum echo audio signals. The proposed extraction phase is carried out in non-blind manner. For this purpose, a calculation is carried out on each frame of host audio signal, in which, the given frame is embedded with |0〉 and |1〉, separately, the sum of the absolute values of differences between corresponding frame of received watermarked quantum audio signal and these two calculated frames is computed. The lower sum of absolute differences indicates the correct embedded qubit in the corresponding frame. The embedding and extraction processes are implemented using quantum reversible circuits, on nanoscale. The proposed scheme has a payload of 512 at SNR = 60.31. The simulation results show that the proposed scheme has high robustness against quantum signal processing attacks.
In this paper, we construct the spot communication method using a stereo speaker. In our proposed method, one speaker transmits differential binary phase-shift keying (DBPSK) symbols for communication, and the other speaker transmits sine waves whose frequency is close to that of the DBPSK symbols for jamming. Inside the spot, the jamming signal is canceled by the orthogonality of the communication symbols and jamming signals. Outside the spot, the jamming signal inverts the differential phase of the communication symbols, which prevents normal DBPSK demodulation rendering the communication symbols concealed in the area. This enables correct demodulation only inside the spot. In the conventional method using a stereo speaker, the effect of the jamming signal is weak; thus, transmitting at least 11 symbols is required. In our proposed method, the effective jamming using the interference between sine waves of close frequencies enables spot communication by transmitting only 3 symbols. In the evaluation experiments, we generate the spot from −10 to 20 degrees in a real environment and measure the signals at 9 positions inside and outside the spot, from −40 to 40 degrees at 10 degree intervals. The measurements were conducted 100 times at each position. Through these experiments, we confirmed that demodulation errors occur only outside the spot. In the measurement results, some systematic errors of the differential phase were observed inside the spot, where theoretically this error should not occur. To discuss this error, we conducted additional experiments and revealed the causes.
Image steganography is a procedure of hiding any messages within an image. In this paper, our major goal is to conceal images within audio, and we converted this audio steganography problem to image steganography by utilizing the mel-spectrogram of the audio files as the cover medium. Previously, this audio steganography problem was implemented using statistical methods like least significant bit (LSB) encoding. Here we explore the use of deep neural networks (DNNs), and we propose a new technique to hide images within the audio using deep generative models which allow us to optimize the perceptual quality of the reconstructed audio and image by our model. We showed that our model efficiently hides images within audio and evades detection by steganalysis tools, is robust to different color spectrum images, and can hide multiple image data in single audio.
This paper utilizes deep neural networks for robust digital watermarking and authentication of speech signals. We present two adversarial neural networks, called embedder and detector. The embedder network tends to achieve imperceptible watermark embedding by minimizing the differences between the original and watermarked signals. The detector strives towards errorless watermark detection. We have proposed joint optimization of these two networks to achieve a trade-off between these requirements. Two models are trained, one with raw speech signals and another with STFT signal representations. Proposed techniques are tested on attacked audio recordings with measures such as SNR, PESQ, BER, and bps. The proposed system achieves high robustness to common watermarking attacks with BERs well below 1%. SNR values greater than 38 dB and PESQ values of 4.33 demonstrate that the difference in original and watermarked signals is negligible. In comparison with other approaches, our scheme shows good overall performance in terms of imperceptibility, robustness, and capacity.
Protecting the Intellectual Property Rights (IPR) associated to Deep Neural Networks (DNNs) is a pressing need pushed by the high costs required to train such networks and by the importance that DNNs are gaining in our society. Following its use for Multimedia (MM) IPR protection, digital watermarking has recently been considered as a mean to protect the IPR of DNNs. While DNN watermarking inherits some basic concepts and methods from MM watermarking, there are significant differences between the two application areas, thus calling for the adaptation of media watermarking techniques to the DNN scenario and the development of completely new methods. In this paper, we overview the most recent advances in DNN watermarking, by paying attention to cast them into the bulk of watermarking theory developed during the last two decades, while at the same time highlighting the new challenges and opportunities characterising DNN watermarking. Rather than trying to present a comprehensive description of all the methods proposed so far, we introduce a new taxonomy of DNN watermarking and present a few exemplary methods belonging to each class. We hope that this paper will inspire new research in this exciting area and will help researchers to focus on the most innovative and challenging problems in the field.
Desynchronization is a very challenging type of attack in audio watermarking. The traditional singular value decomposition (SVD) based audio watermarking methods embed the watermark information by modifying the singular value of individual segment, which have little resistance against desynchronization attacks. In this paper, we propose a novel frequency singular value coefficient (FSVC) feature, which reflects the ratio between the singular values of two consecutive segments and is insensitive to desynchronization attacks, to carry the watermark bits. To our best knowledge, it is the first time that the ratio between singular values is employed for audio watermarking. In the proposed method, the discrete cosine transform (DCT) is performed on two consecutive segments of the host audio signal and SVD is applied to the DCT coefficients of the mid frequency band of each segment to extract the FSVC. Then the watermark bits are embedded by adjusting the values of the FSVC. The watermark embedding procedure is optimized to minimize the perceptual quality degradation and an error buffer is created to enhance the robustness. As a result, the proposed method can achieve a much higher embedding capacity than the existing methods tackling desynchronization attacks. The impact of desynchronization and common signal processing attacks on the proposed watermarking method is mathematically modeled, and the effectiveness of the proposed method against these attacks is theoretically and experimentally validated.
In the current era of digital technology, the information security is the challenging task. For the secrete communication information hiding is an essential element. The current information steganography system uses objects like audio, image and video. The audio steganography is the technique that convey hidden message by modifying an audio signal in an unnoticeable manner. It is a technique for the hiding secret message in the host audio signal. The original audio message before steganography and after encoding message is having uniform characteristics. The embedding secrete audio message in the original audio file is a more challenging and difficult task. This paper presents the comprehensive survey of audio steganography techniques for information security. The experiment was tested using proposed LSB technique for audio steganography. This paper extended towards quality measure of steganography message. The quality of audio steganography measures using energy score, Mean square error, Peak signal to noise ratio. From this experiment the quality of audio steganography is observed as 92.759% for MSE and 94.971% for PSNR technique. Audio information hiding is the one of the robust and dynamic ways of protecting the privacy and secretes communication.
Embedding data into a given medium is called Steganography, in such a way that it cannot be detected in a given image. Also, cloud computing has altered the way information is accessed, stored, and transmitted; the emphasis is in making the data more robust and keeping it hidden within a given image. The current techniques of spatial embedding do not deliver the robustness that is needed for basic compression algorithms. To produce a better method, it takes the help of the least-significant bit paradigm (Wayner, Disappearing cryptography: information hiding: steganography and watermarking. 3rd ed. Morgan Kaufmann Publishers, Burlington, 2009; Gruhl and Bender, Echo hiding. In: Proceeding of information hiding workshop, p. 295–315, 1996). With this paradigm, we are led towards the idea of transforming the embedding system from the very beginning, which is to hide the data in the domains of frequency. The following paper proposes a method of transform embedding which uses current digital encryption methods and improves the steganography results by using the empirical data, and the encrypted image is deployed in the cloud to be used from anywhere. This method is more robust than the existing spatial embedding methods. The claims are backed by the experimental results which are shown in the paper.
In this chapter, we propose a new information hiding and extraction scheme for the application in digital watermarking, which does not embed any data to target content, by using non-linear feature extraction scheme trained on frequency domain. This is done by processing the selected coefficients from the selected feature sub-blocks as an input vector to the trained neural network and observing output signal from the neural network. This output signal is used as watermark signal which distinguishes its image from other images. This model trains an artificial neural network to assign predefined secret code for corresponding input feature vector of an image and use this trained artificial neural network weight and the coordinates of the selected feature sub-blocks as a key to extract the predefined secrete code.The proposed method contributes to secure image digital watermarking for content identification without damaging or losing any detailed data of visual images. The features of our proposed method employ an application to authenticate multimedia, similarity comparison, verification of image integrity and copyright protection of multimedia contents.
In this paper, the authors propose information hiding by machine learning: a method of key generation for information extracting using neural network. The method consists of three layers for information hiding. First, the proposed method prepares feature extraction keys, which are saved by feature extraction attributes like feature coordinates and the region of frequency coefficients. Second, the proposed method prepares hidden patterns in advance to the embedding procedure as a watermark signal of the target contents. Finally, the proposed method generates information extraction keys by using machine learning to output presented hidden patterns. The proper hidden patterns are generated with the proper information extraction key and feature extraction key. In the experiments, the authors show that the proposed method is robust to high pass filtering and JPEG compression. The proposed method contributes to secure visual information hiding without damaging any detailed data of the target content.
In this chapter, we propose a new information hiding and extraction scheme for the application in digital watermarking, which does not embed any data to target content, by using non-linear feature extraction scheme trained on frequency domain. This is done by processing the selected coefficients from the selected feature sub-blocks as an input vector to the trained neural network and observing output signal from the neural network. This output signal is used as watermark signal which distinguishes its image from other images. This model trains an artificial neural network to assign predefined secret code for corresponding input feature vector of an image and use this trained artificial neural network weight and the coordinates of the selected feature sub-blocks as a key to extract the predefined secrete code.The proposed method contributes to secure image digital watermarking for content identification without damaging or losing any detailed data of visual images. The features of our proposed method employ an application to authenticate multimedia, similarity comparison, verification of image integrity and copyright protection of multimedia contents.
This chapter presents a method of aerial acoustic communication in which data is modulated using OFDM (Orthogonal Frequency Division Multiplexing) and embedded in regular audio material without significantly degrading the quality of the original sound. It can provide data transmission of several hundred bps, which is much higher than is possible with other audio data hiding techniques. The proposed method replaces the high frequency band of the audio signal with OFDM carriers, each of which is power-controlled according to the spectrum envelope of the original audio signal. The implemented system enables the transmission of short text messages from loudspeakers to mobile handheld devices at a distance of around 3m. This chapter also provides the subjective assessment results of audio clips embedded with OFDM signals.
Audio watermarking plays an important role in copyright protection. Echo hiding, one of the most effective techniques for audio watermarking, has been studied for decades. However, the conventional echo hiding has been criticized for its weak security, as watermarks can be easily extracted by means of cepstrum analysis even without any prior knowledge. This paper explores the time-frequency (T-F) characteristics of the repetition structures in an audio signal to improve the security of conventional echo hiding. In our approach, the original audio signal is first converted into a high-dimensional T-F representation, and then by clustering the time frames that have similar T-F characteristics into the same subspace, the original audio is decomposed into a union of subspaces with each corresponding to one time-domain subsignal. Paired and opposite echo kernels are applied to energy-balanced subsignals for watermark embedding, which significantly improves the security. In the watermark extraction process, the subspaces are recovered on the basis of the T-F similarities and cepstrum analysis is utilized to extract watermarks. The proposed embedding and extraction schemes thus offer a new approach for echo hiding. The results of experiments demonstrate the effectiveness of our approach with respect to inaudibility, security, and robustness.
This paper proposes a method for hiding information in audio signals by using singular spectrum analysis (SSA) with a psychoacoustic model to enhance the sound quality of a watermarked signal from our previous work. In this framework, an original signal is decomposed into many sub-signals by applying the combination of the SSA-based method and the psychoacoustic model. The sub-signals to be embedded are chosen using signal analysis based on human perception. The watermark bits are embedded into selected sub-signals by modifying some parts of their singular spectra according to an embedding rule. Then, the accuracy of extracted watermark bits and the sound quality of the watermarked signal, compared with that of the original one, are used to verify the performance of our framework. The experimental results show that the proposed framework satisfies the evaluation criteria in terms of inaudibility and robustness. However, it has a significant trade-off between them.
Now a days, cases of theft of important data both by employees of the organization and outside hackers are increasing day-by-day. So, new methods for information hiding and secret communication are need of today. Steganography is an option for it. Embedding a secret message into other meaningful message (cover media) without disturbing the features of the cover media is known as steganography. A novel approach for audio steganography is proposed in this paper. Here, secret message and cover media both are digital audio. Proposed approach is robust with respect to both LSB removal and re-sampling attacks. This approach adds extra layer of security because a transformation function is applied on amplitude bits of secret audio before embedding. This approach is more resistive towards white Gaussian noise addition (WGN) during transmission of stego file. The proposed approach is also suitable for embedding secret audio during real time audio communication because processing time is low while embedding capacity is high. Embedding capacity of the proposed approach is same as of conventional LSB approach because in both approaches one bit of secret is being inserted in each sample of cover audio. Standard parameters: Perceptual Evaluation of Speech Quality (PESQ) and Mean Opinion Score (MOS) are used for measuring the imperceptibility between cover audio & stego audio. For the proposed approach, PESQ and MOS are found as 4.47 and 5 that are very close to their respective highest values 4.5 and 5 when there is no attack.
Background & Objective
SVD based audio watermarking schemes met the requirements of imperceptibility, having moderate payload and are robust to most common signal processing attacks. But, when the watermarked audios are compressed at higher compression i.e. compression at lower bit rate, the percentage retrieval of the watermark is reduced. Since the audios posted on the networked environment i.e. world wide web (www) are mostly Mp3 audios compressed at different compression rate, there is a need to develop a watermarking scheme which is inherently robust to compression attack at different bit rates.
Methods
Scheme presented in this paper uses a two phase approach for embedding the watermark. The proposed scheme is having a high payload and is inherently robust to compression attack. In the proposed scheme, watermarked audios are made inherently robust to mp3 compression at different bit rates and common signal processing attacks through selection of embedding frames that resist the attacks fully.
Results & Conclusion
A preliminary analysis of mp3 attack on the individual frames is done prior to finally embedding the watermark for ensuring robustness to mp3 compression and other attacks.
Steganografi, bir verinin herhangi bir taşıyıcı içerisine gizlenerek güvenli bir şekilde iletilmesini sağlayan yöntemleri araştıran bilim dalıdır. Steganografi yöntemleri genel olarak resim, ses ve video gibi dijital verilerin kopya koruma amaçlı damgalamasında kullanılmaktadır. İnsanın işitme duyusu görme duyusuna kıyasla çok daha hassas olduğu için ses steganografi oldukça zorlu bir alandır. Dolayısıyla, ses steganografi ile ilgili yayınların sayısı resimlere kıyasla daha azdır ve nitelikli çalışmalar oldukça karmaşık algoritmalar üzerine kuruludur. Bu tez çalışmasında yaygın olarak kullanılan seçilmiş ses steganografi yöntemleri ve karşılaştırmaları, matematiksel olarak ve dijital sinyal işleme temelleri ile birlikte yalın bir şekilde açıklanmaya çalışılmıştır. Çalışmanın asıl hedefi mevcut temel yöntemlerden oluşan açık kaynak kodlu bir kütüphane tasarlayıp, paylaşabilmektir. Bu kütüphane tasarımı için, bilimsel araştırmalarda yaygın olarak kullanımı göz önünde bulundurularak MATLAB platformu tercih edilmiştir. Bu çalışmada özellikle Tayf Yayılımı, Yankı Veri Gizleme ve Önemsiz Bit Kodlaması yöntemleri üzerine odaklanılmıştır. İncelenen yöntemler için karşılaştırmalar sağlamlık, kapasite ve fark edilmezlik üçgeni içerisinde değerlendirilmiştir. Yöntemlerin sağlamlıkları sıkıştırmaya karşı başarı oranları ile tartışılıp, sonuç olarak Tayf Yayılımı yöntemi üzerinde bir takım performans iyileştirmeleri önerilmiştir.
Steganography is a popular technique of digital data security. Among all digital steganography methods, audio steganography is very delicate as human auditory system is highly sensitive to noise; hence small modification in audio can make significant audible impact. In this paper, a key based blind audio steganography method has been proposed which is built on discrete wavelet transform (DWT) as well as discrete cosine transform (DCT) and adheres to Kerckhoff’s principle. Here image has been used as secret message which is preprocessed using Arnold’s Transform. To make the system more robust and undetectable, a well-known problem of audio analysis has been explored here, known as Cocktail Party Problem, for wrapping stego audio. The robustness of the proposed method has been tested against Steganalysis attacks like noise addition, random cropping, resampling, requantization, pitch shifting, and mp3 compression. The quality of resultant stego audio and retrieved secret image has been measured by various metrics, namely, “peak signal-to-noise ratio”; “correlation coefficient”; “perceptual evaluation of audio quality”; “bit error rate”; and “structural similarity index.” The embedding capacity has also been evaluated and, as seen from the comparison result, the proposed method has outperformed other existing DCT-DWT based technique.
Steganography is a means of covert communication without revealing the occurrence and the real purpose of communication. The adaptive multirate wideband (AMR-WB) is a widely adapted format in mobile handsets and is also the recommended speech codec for VoLTE. In this paper, a novel AMR-WB speech steganography is proposed based on diameter-neighbor codebook partition algorithm. Different embedding capacity may be achieved by adjusting the iterative parameters during codebook division. The experimental results prove that the presented AMR-WB steganography may provide higher and flexible embedding capacity without inducing perceptible distortion compared with the state-of-the-art methods. With 48 iterations of cluster merging, twice the embedding capacity of complementary-neighbor-vertices-based embedding method may be obtained with a decrease of only around 2% in speech quality and much the same undetectability. Moreover, both the quality of stego speech and the security regarding statistical steganalysis are better than the recent speech steganography based on neighbor-index-division codebook partition.
Several improvements to the time-spread echo hiding method are proposed for an aerial audio data hiding in which speech signals are broadcast by the outdoor loudspeakers of a voice evacuation and mass notification system. Evaluations of the data hiding system for speech signals were conducted using computer simulations including several disturbances caused by the long-distance (from 70 to 800 m) aerial transmission of sounds. The frequency response of a distant horn-array loudspeaker system, the absorption of sound by the atmosphere, reverberation and a single long-path echo, a constant frequency shift that mimics a small Doppler shift and a mismatch of sampling frequencies between sending and receiving devices, and additive background noise are simulated as disturbances. A background noise recorded outdoors was mixed to simulate a loud outdoor space in a city at signal-to-noise ratios of −5, 0, and 5 dB. The computer simulation results showed that the suppression of high- and low-frequency regions in the logarithmic spectral domain in the decoding process was significantly effective for the decoding performance. A novel hiding method of the alternating sign of echoes was moderately effective under relatively high SNR (0 and 5 dB) conditions.
This paper proposes an evaluation framework for an audio data hiding system that can be used for long-distance aerial transmissions where the stego speech signal is emitted by outdoor loudspeakers of voice evacuation and mass notification systems. Typical disturbances of aerial transmissions are modeled and implemented by signal processing units in series. The results of computer simulations for long-distance (70–800 m) aerial transmissions show that a bilateral time-spread echo hiding combined with a novel frame synchronization technique exhibits better detection performance than the conventional time-spread echo hiding under extremely low signal-to-noise ratios of 0 and −5 dB. Moreover, high-frequency attenuation and frequency shifts at the receiving side degrade the detection performance of the time-spread echo hidings.
This paper aims to develop a desktop application system called E-Sign detector using image steganography. It targets to fulfill the requirements of small and medium size companies to identify their employers through a specially designed embedded picture employee ID card. This employee ID card will be able to track the employee when he/she is attempting to enter through a doorway of the company. Hence, this will be highly advantageous for small companies where it is needed to grant special privileges to a certain number of officers to enter a high defensive area. This application will be a real-time system with higher reliability that saves time and decreases the manpower usage and provides higher security. Through this system, the company can mark the time at which an employee is accessing a certain place and leaving that place, and maintain daily attendance automatically. Finally, we argue that the proposed system will be a good substitution for the replacement of manual employee identification system as we have implemented and solved the drawbacks found in a manual employee identification system.
This chapter introduces a state-of-the-art scheme of non-blind digital-audio watermarking, based on the properties of the human cochlear. It is based on the concept of embedding inaudible watermarks into an original sound by controlling its phase characteristics in relation to the characteristics of Cochlear Delay (CD). Inaudible watermarks are embedded into original signals by applying Infinite Impulse Response (IIR) all-pass filters with CDs and they are then extracted from the phase difference between the original and watermarked sounds. The results obtained from objective and subjective evaluations and robustness tests revealed that the CD-based approach is considerably more effective in satisfying the requirements for non-blind inaudible watermarking. Embedding limitations with the CD-based approach were investigated with various evaluations. These results also revealed that embedding limitations with the CD-based approach could be improved by using parallel, cascade, and composite architectures for the CD filters.
In recent years, there has been considerable interest in the development of audio watermarking techniques. To clarify the essential principles underlying a diversity of sophisticated algorithms, this chapter gives an overview of basic methods for audio watermarking, such as least significant bit (LSB) modification, phase coding, spread spectrum watermarking, cepstrum domain watermarking, wavelet domain watermarking, echo hiding, and histogram-based watermarking.
In this paper a new method for information hiding in club music is introduced. The method called StegIbiza is based on using the music tempo as a carrier. The tempo is modulated by hidden messages with a 3-value coding scheme, which is an adoption of Morse code for StegIbiza. The evaluation of the system was performed for several music samples (with and without StegIbiza enabled) on a selected group of testers who had a music background. Finally, for the worst case scenario, none of them could identify any differences in the audio with a 1% margin of changed tempo.
Audio watermarking is a well-known technique of hiding data through audio signals. It is also known as audio steganography and has received a wide consideration in the last few years. So far, several techniques for audio watermarking have been discussed in the literature by considering different applications and development positions.
In echo hiding, watermark data is embedded into the host signal by introducing echoes of different delays. The information is extracted by estimating the delays and amplitudes of the echoes in the test signal using cepstral analysis. If the delay between the original and the echo is below the just noticeable difference for the human ear and the relative amplitude of the echo is below a certain threshold, then the resultant signal is perceptually identical to the original. This basic technique has then been improvised using the bipolar echo kernel and extended bipolar echo kernel, which use echoes with positive and negative amplitudes, to achieve better performance in terms of fidelity and robustness. We study the problem of temporal offset in the context of extended bipolar kernel based audio watermarking, and a solution based on overlapped frames and long term averaging is proposed. Further, we present the results of our experiments—conducted on an ensemble of 250 audio signals of various genres and styles—to verify the performance of the proposed watermarking system.
Digitale Wasserzeichen sind eine Methode, Zusatzdaten - für den Menschen nicht wahrnehmbar - in Multimediadaten einzubetten. Im Bereich der Audiowasserzeichen arbeiten die meisten Systeme mit nichtkomprimierten Daten als Eingangssignal. Einige wenige Verfahren jedoch sind in der Lage, Wasserzeichen direkt in bereits komprimiertes Audiomaterial einzubetten. In diesem Beitrag werden nach einem kurzen Überblick über verschiedene Wasserzeichenmethoden zwei Verfahren vorgestellt, die - zueinander kompatibel - Wasserzeichen in unkomprimierte und komprimierte Audiosignale einbetten können. Die Funktionsweise der Verfahren, der derzeitige Stand der Entwicklung sowie die Leistung der Verfahren werden dargestellt.
The previous chapter briefly discussed the application and properties of digital watermarking, outlined the motivation, and the organization of the book. This chapter presents some existing popular audio watermarking methods and some transformation and decomposition techniques used in the proposed watermarking methods.
Data hiding, a form of steganography, embeds data into digital media for the purpose of identification, annotation, and copyright. Several constraints affect this process: the quantity of data to be hidden, the need for invariance of these data under conditions where a "host" signal is subject to distortions, e.g., lossy compression, and the degree to which the data must be immune to interception, modification, or removal by a third party. We explore both traditional and novel techniques for addressing the data-hiding process and evaluate these techniques in light of three applications: copyright protection, tamper-proofing, and augmentation data embedding.
A compression standard that uses motion estimation and DCT technology to achieve high efficiency is called the MPEG standard. This standard is complex enough to be adapted to many different video applications.
Techniques for Data Hiding
- W Bender
- D Gruhl
- N Morimoto
- W. Bender