Adaptive Audio Steganography Based on Advanced Audio Coding and Syndrome-Trellis Coding

In this paper, we describe the implementation of the multi-channel AAC encoder system for digital audio broadcasting. The encoder system is based on MPEG-2/4 advanced audio coding (AAC) and is capable of real-time encoding up to 5.1 channel audio. To give a flexible functionality, it consists of multiple DSPs, IEC61937 and TCP/IP interface and 6 channel audio input facilities. The reference AAC decoder was implemented for verification test of the encoder. The encoder system is also integrated with the AAC streaming system for interoperation test. Through these tests, the encoder system is verified to be a good solution for high quality audio broadcasting.

In this paper, we develop a 3D audio reproduction scheme for the purpose of delivering audio over IP networks. In this scheme, audio streams constructed at a server are composed of the TCP/IP header followed by multi-channel audio data compressed by MPEG advanced audio coding (AAC), and the decoded audio signals are played out on a stereo loudspeaker system at the client. Since the audio source is recorded by a multi-channel microphone but the playout is dedicated to stereo speakers, the quality mismatch between the multi-channel and the stereo system should be overcome. As a potential solution, we first investigate the effect of 3D audio processing on the audio quality at the client by applying a head-related transfer function (HRTF). Next, a crosstalk cancellation process is applied to the audio with 3D effects in order to improve the immersion of the processed 3D effects on a stereo loudspeaker system. Finally, we evaluate the performance of the 3D audio reproduction system in terms of the identification of an audio source and quality comparison before and after applying the crosstalk cancellation technique.

MPEG-4 scalable lossless (SLS) coding is a unified solution for demands in high compression perceptual audio and high quality lossless audio. It provides a fine-grain scalable extension to the MPEG-4 advanced audio coding (AAC) perceptual audio coder up to fully lossless reconstruction. It is observed that the quality of SLS coded audio is still far from optimal when the core bitrate is low. With this observation, an adaptive bit-plane scanning (ABPS) method is proposed in this paper. In ABPS, the bit-plane scanning order is adaptive to the energy distribution of the signal to be coded. The results show that with ABPS, the perceptual quality of the audio under low core bitrate scenario is significantly improved without any extra payload.

Given the popularity of audio and video applications, compressed audio has become an important carrier of covert communication on the Internet. Many novel compressed audio steganography schemes have emerged that offer good hiding capability and aural concealment. In this paper, a universal steganalysis scheme called MultiSpecNet is proposed to detect steganography based on multiple embedding domains (advanced audio coding (AAC) and MPEG-1 Audio Layer III (MP3)), which are currently the two most popular compressed audio standards. The basic idea is that modification of either domain by a steganography scheme will change the time-frequency relationship of the audio signal after decoding. The proposed approach adopts the spectrogram as the input feature to extract richer information. DeepResNet is used to learn the distinguishing feature representations, and multiscale spectrograms are used to enrich the feature diversity. The experimental results show that the proposed scheme is effective at detecting different steganography schemes based on the AAC and MP3 embedding domains. The detection accuracy of the proposed scheme is higher than that achieved by other state-of-the-art schemes. Using spectrograms as the input, DeepResNet achieves better performance than schemes using quantized modified discrete cosine transform (MDCT) coefficients and mel-spectrogram, although the quantized MDCT coefficient is the parameter modified by the steganography schemes directly and mel-spectrogram is very popular and effective for general audio signal analysis. To the best of our knowledge, this work is the first audio steganalysis scheme that can detect multiple steganography schemes in both the MP3 and AAC embedding domains. The method proposed in this paper can be extended to audio steganalysis for other codecs or for audio forensics purposes.

We propose a frame loss concealment technique for decoders compatible with MPEG advanced audio coding (AAC). The spectral information of the lost frame is estimated in the modified discrete cosine transform (MDCT) domain via efficient techniques that are tailored to individual source signal components: in noise-like spectral bins the MDCT coefficients are obtained by shaped-noise insertion, while coefficients in tone-dominant bins are estimated by frame interpolation followed by a refinement procedure so as to optimize the fit of the concealed frames with neighboring frames. Experimental results demonstrate that the proposed technique offers performance superior to techniques adopted in commercial AAC decoders.

Enhanced aacPlus is an audio codec which is composed of advanced audio coding (AAC), spectral band replication (SBR), and parametric stereo (PS) for efficient audio coding at low bit rates. We propose a new coding scheme for lossless bit rate reduction of PS in enhanced aacPlus. We first determine the optimal contexts for context-based coding of quantized stereo parameter indexes in PS. Then we propose a coding scheme which is based on context-based coding using the determined optimal contexts in conjunction with arithmetic coding. The proposed scheme has normal and memory-reduced versions, both of which are shown to guarantee significant and consistent lossless bit rate reduction of PS. The saved bits by the proposed scheme can be used for the other modules of enhanced aacPlus, AAC and SBR.

Steganography is used to hide the occurrence of communication. This creates a potential problem when this technology is misused for planning criminal activities. Differentiating anomalous audio document (stego audio) from pure audio document (cover audio) is difficult and tedious. This paper investigates the use of a Genetic-X-means classifier, which distinguishes a pure audio document from the adulterated one. The basic idea is that, the various audio quality metrics (AQMs) calculated on cover audio signals and on stego-audio signals vis-a-vis their denoised versions, are statistically different. Our model employs these AQMs to steganalyse the audio data. Genetic paradigm is exploited to select the AQMs that are sensitive to various embedding techniques. The classifier between cover and stego-files is built using X-means clustering on the selected feature set. The presented method can not only detect the presence of hidden message but also identify the hiding domains. The experimental results show that the combination strategy (Genetic-X-means) can improve the classification precision even with lesser payload compared to the traditional ANN (Back Propagation Network).

This paper presents a novel parametric vector quantization (PVQ) scheme as the secondary encoding to code perceptually salient percussive sounds such as drums in the time domain. It is deployed to improve the quality of service in the case of packet losses during percussive events. As a generalization and an improvement of our earlier system, the new scheme can achieve a better balance between bandwidth efficiency and error robustness. The proposed coding technique has been implemented with the MPEG-2 AAC (advanced audio coding) frame structure. Experimental results with music samples have shown the effectiveness of the proposed scheme.

A magnetron is a power oscillator device used in several radar transmitters for generating the electromagnetic wave (EMW) with a constructive and fixed frequency. In this work, a radar transmitter has been carried out using magnetron operates at 2,458 MHz and two conducting layers waveguides to achieve minimum loss of the signal due to the increased temperature. The magnetron is connected with the high voltage capacitor (1.0 μF) in order to store the alternating current (AC) signal delivered from the high voltage transformer. A waveguide parts have been used as transmission lines in view of connecting the magnetron to the antenna. These parts include two metal layers, the upper layer (outer) is advanced audio coding (AAC) 1350 aluminum conductor and the lower (inner) is copper. The waveguide dimension should be suitable to flow frequency from 2.2 GHz to 3.3 GHz. To measure the operating frequency, a waveguide adapter and a coaxial cable which combined with n-female connector have been connected to magnetron. The wave is delivering to the frequency counter by Bayonet Neill–Concelman (BNC) to n-female connectors. The promising results of the proposed work have been achieved with a maximum power, efficient return loss, acceptable voltage standing wave ratio (VSWR) and low-cost manufacturing.

In the hybrid video coding framework, quantization is the key technique to achieve lossy compression. The information loss caused by the quantization may be reduced to improve compression efficiency, by using either encoder-side rate-distortion optimized quantization or decoder-side filtering. Nonetheless, the existing studies did not extensively use the already encoded information, i.e., context, to reduce the quantization loss. We address this issue and propose a context-adaptive inverse quantization method, namely, CAIQ. Specifically, for inter-frame coding, we analyze the correlation between the prediction signal (generated by motion compensated prediction) and the residual signal, as well as the correlation within the residual signal itself. We then present linear as well as nonlinear yet lightweight models to exploit the observed correlations in the frequency domain. Our models provide an optional inverse quantization mode by referring to the prediction signal, which is available at the decoder side. Next, block-level mode selection regarding the CAIQ method is used at the encoder side. We integrate the proposed CAIQ method into the reference software of Versatile Video Coding. We perform an extensive study of the models and analyze their resulting compression efficiency gain and encoding/decoding complexity. Experimental results show that our CAIQ method improves compression performance especially for high-resolution videos and at high bit rates.

This paper proposes a new MPEG-2 AAC Huffman decoding algorithm which is designed to find multiple symbols in a single search. The analysis and experimental results show that the computational complexity of the proposed method is lower by more than 46% when compared with those of the up-to-date methods.

A scalable audio coding method is proposed using a technique, Quantization Index Modulation, borrowed from watermarking. Some of the information of each layer output is embedded (watermarked) in the previous layer. This approach leads to a saving in bitrate while keeping the distortion almost unchanged. This makes the scalable coding system more efficient in terms of Rate-Distortion. The results show that the proposed method outperforms the scalable audio coding based on reconstruction error quantization which is used in practical systems such as MPEG-4 AAC.

The least-significant-bit based approach is a popular type of stenographic algorithms in the spatial domain. However, we find that in most existing approaches, the choice of embedding positions within a cover audio mainly depends on a pseudorandom number generator without considering the relationship between the audio content itself and the size of the secret message. In this paper, we expand the least significant bit matching revisited audio stegnography and propose an edge adaptive scheme which can select the embedding regions according to the size of secret message and the difference between two consecutive pixels in the cover audio. For lower embedding rates, only sharper edge regions are used while keeping the other smoother regions as they are. When the embedding rate increases, more edge regions can be released adaptively for data hiding by adjusting just a few parameters. New scheme can enhance the security significantly compared with typical least significant bit-based approaches as well as their edge adaptive ones, such as pixel-value-differencing-based approaches, while preserving higher visual quality of stegno audios at the same time.

The purpose of this paper is mainly aimed to provide an energy security strategy for the petroleum production and processing in the grand challenges. Fault detection and diagnosis is the central component of abnormal event management (AEM) [1]. According to the International Federation of Automatic Control (IFAC), a fault is defined as an unpermitted deviation of at least one characteristic property or parameter of the system from the acceptable/usual/standard condition [2-4]. Generally, there are three parts in a fault diagnosis system, detection, isolation, and identification [5, 6, 7]. Depending on the performance of fault diagnosis systems, they are called FD (for fault detection) or FDI (for fault detection and isolation) or FDIA (for fault detection, isolation and analysis) systems [5]. As the increasing needs for energy grows rapidly, energy security becomes an important issue especially in petroleum production and processing. The importance can be mainly considered in following perspectives: higher system performance, product quality, human safety, and cost efficiency [5, 8]. With this in mind, the purpose of this research is to develop a Fault Detection and Isolation (FDI) system which is capable to diagnosis multiple sensor faults in nonlinear cases. In order to lead this study closer to real world applications in oil industries, the system parameters of the applied system are assumed to be unknown. In the first step of the proposed method, phase space reconstruction techniques are used to reconstruct the phase space of the applied system. This step is aimed to infer the system property by the collected sensor measurements. The second step is to use the reconstructed phase space to predict future sensor measurements, and residual signals are generated by comparing the actually measured measurements to the predicted measurements. Since, in practice, residual signals will not perfectly equal to zero in the fault-free situation, Multiple Hypothesis Shiryayev Sequential Probability Test (MHSSPT) is introduced to further process those residual signals, and the diagnostic results are presented in probability. In addition, the proposed method is extended to a non-stationary case by using the conservation/dissipation property in phase space. The proposed method is examined by both of simulated data and real process data. The three tank model is modeled according to a nonlinear laboratory setup DTS200 and introduced for generating simulated data. On the other hand, the real process data collected from a sugar factory actuator system are also used to examine the proposed method. According to our results obtained from simulations and experiments, the proposed method is capable to indicate both of healthy and faulty situations. In the end, we have to emphasize that the proposed approach is not limited in the applications of petroleum production and processing. For example, our approach can also apply to enhance the quality of water and avoid the discharges, such as leakage, in the process of water resource management. Therefore, the proposed approach not only benefits the issue of energy security but also other issues in the grand challenges.

In this work an efficient method for hiding a speech in audio is proposed. The features of secretspeech is extracted with LPC (Linear Predictive Coding), and these parameters embedded in audio inchaotic order. Discrete Wavelet Transform (DWT) is applied on audio frames to split the signal in high andlow frequencies. The embedding parameters are embedded in high frequency. The stego audio isperceptually indistinguishable from the equivalent cover audio. The proposed method allows hiding a sameduration of speech (secret) and audio (cover). The stego audio is subjected to objective tests such signal to noiseratio (SNR), signal to noise ratio segmental (SNRseg), Segmental Spectral SNR, Log Likelihood Ratio (LLR)and Correlation (Rxy) to determine the similarity with original audio.