Detection and localization of double compression in MP3 audio tracks

In this work, by exploiting the traces left by double compression in the statistics of quantized modified discrete cosine transform coefficients, a single measure has been derived that allows to decide whether an MP3 file is singly or doubly compressed and, in the last case, to devise also the bit-rate of the first compression. Moreover, the proposed method as well as two state-of-the-art methods have been applied to analyze short temporal windows of the track, allowing the localization of possible tampered portions in the MP3 file under analysis. Experiments confirm the good performance of the proposed scheme and demonstrate that current detection methods are useful for tampering localization, thus offering a new tool for the forensic analysis of MP3 audio tracks

AMR Compressed-Domain Analysis for Multimedia Forensics Double Compression Detection

An audio recording must be authentic to be admitted as evidence in a criminal prosecution so that the speech is saved with maximum fidelity and interpretation mistakes are prevented. AMR (adaptive multi-rate) encoder is a worldwide standard for speech compression and for GSM mobile network transmission, including 3G and 4G. In addition, such encoder is an audio file format standard with extension AMR which uses the same compression algorithm. Due to its extensive usage in mobile networks and high availability in modern smartphones, AMR format has been found in audio authenticity cases for forgery searching. Such exams compound the multimedia forensics field which consists of, among other techniques, double compression detection, i. e., to determine if a given AMR file was decompressed and compressed again. AMR double compression detection is a complex engineering problem whose solution is still underway. In general terms, if an AMR file is double compressed, it is not an original one and it was likely doctored. The published works in literature about double compression detection are based on decoded waveform AMR files to extract features. In this paper, a new approach is proposed to AMR double compression detection which, in spite of processing decoded audio, uses its encoded version to extract compressed-domain linear prediction (LP) coefficient-based features. By means of feature statistical analysis, it is possible to show that they can be used to achieve AMR double compression detection in an effective way, so that they can be considered a promising path to solve AMR double compression problem by artificial neural networks

Improved steganalysis technique based on least significant bit using artificial neural network for MP3 files

MP3 files are one of the most widely used digital audio formats that provide a high compression ratio with reliable quality. Their widespread use has resulted in MP3 audio files becoming excellent covers to carry hidden information in audio steganography on the Internet. Emerging interest in uncovering such hidden information has opened up a field of research called steganalysis that looked at the detection of hidden messages in a specific media. Unfortunately, the detection accuracy in steganalysis is affected by bit rates, sampling rate of the data type, compression rates, file track size and standard, as well as benchmark dataset of the MP3 files. This thesis thus proposed an effective technique to steganalysis of MP3 audio files by deriving a combination of features from MP3 file properties. Several trials were run in selecting relevant features of MP3 files like the total harmony distortion, power spectrum density, and peak signal-to-noise ratio (PSNR) for investigating the correlation between different channels of MP3 signals. The least significant bit (LSB) technique was used in the detection of embedded secret files in stego-objects. This involved reading the stego-objects for statistical evaluation for possible points of secret messages and classifying these points into either high or low tendencies for containing secret messages. Feed Forward Neural Network with 3 layers and traingdx function with an activation function for each layer were also used. The network vector contains information about all features, and is used to create a network for the given learning process. Finally, an evaluation process involving the ANN test that compared the results with previous techniques, was performed. A 97.92% accuracy rate was recorded when detecting MP3 files under 96 kbps compression. These experimental results showed that the proposed approach was effective in detecting embedded information in MP3 files. It demonstrated significant improvement in detection accuracy at low embedding rates compared with previous work

An analysis of strategic management in the digital music industry in a Chinese context

There are elements of cultural innovation only partly articulated in managing the business of Digital Music within academic research in a Chinese context. This thesis research into one question, how far management and operational systems developed with a western background can be applied efficiently to the Chinese context within the field of the Digital Music Industry? The study adopted a chronological approach. It followed the development history of three timelines, the development of management theories and logic in China and the West, the development of global Digital Music, the development of China's Digital Music Industry, which including understanding a critical introduction to management in its historical and intellectual context which provided a useful expansion of the issues raised. This research analyses China's Digital Music Industry from the perspective of the insider, with a people-oriented research angle and a comprehensive methodology based on an interpretive approach combined with dialectical thinking. The research distinguishes China's Digital Music Industry from other mature Digital Music industries and highlights the contemporary challenges it presents in the current context. This thesis begins by building a theoretical framework of Western management and its development, contrasting this with a Chinese experience of theories and philosophy of management. It tested these theories by analysing the changes and growth of Digital Music management in China from the external environment perspective and a case study of QQ Music. The research compares the similarities and differences between China's Digital Music Industry and others which include definitions of Digital Music, historical developments, people's concept of consumption, attitude, and behavioural habits around Digital Music. It reviews the literature on management research to conceptualise Western theories combined with the case study of QQ music, to make explicit how they apply or do not apply in China, and to be more specific, within the Chinese Digital Music Industry. The research defines the mission and goal of Digital Music in a Chinese context. More importantly, based on the analysis to understand the Chinese Digital Music management logic, makes clear the unique attributes (service as the core competitiveness), the development pattern of China's Digital Music Industry (an online and offline interactive digital business ecosystem) and offers a way to extend existing theories (the collision of fan economy, experience economy and the Long Tail theory). The research has collected a lot of valuable first-hand data, including many hard-to-reach groups and includes non-public data from the company and local government. The study concludes that Western management theories are distinct from China's experience in the Digital Music Industry. This lies in, particularly, the core profit model and consumer habits of Digital Music in China and their difference to the West. Consumers have different perceptions of the value of music content and service. It is valuable to seek new insights into advanced business models and management theories which is set to enhance the study of China's Digital Music Industry and which may provide the practical assessment of good practice in a Chinese context to inform management practice from non-Western models