• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.4
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• pp.16-22
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• 2012

In this paper, the forensic marking algorithm is proposed using psychoacoustic model II and MDCT for high-quality audio. The proposed forensic marking method, that inserts the user fingerprinting code of the audio content into the selected sub-band, in which audio signal energy is lower than the spectrum masking level. In the range of the one frame which has 2,048 samples for FFT of original audio signal, the audio forensic marking is processed in 3 sub-bands. According to the average attack of the fingerprinting codes, one frame's SNR is measured on 100% trace ratio of the collusion codes. When the lower strength 0.1 of the inserted fingerprinting code, SNR is 38.44dB. And in case, the added strength 0.5 of white gaussian noise, SNR is 19.09dB. As a result, it confirms that the proposed audio forensic marking algorithm is maintained the marking robustness of the fingerprinting code and the audio high-quality.

• Journal of Digital Contents Society
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• v.15 no.3
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• pp.357-363
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• 2014

In this paper, we propose a new audio forensic marking system for protecting the copyright of the Internet-based music streaming services. In the proposed method, in order to guarantee the QoS of the streaming service, high speed, and generates a forensic mark inserted MP3 file. We make pre-marking process and generate a new forensic marked MP3 file, a combination of the pre-marked MP3 frame, the inserted user information. Experimental results show that the proposed method satisfactory results robustness and imperceptibility, and real-time properties. In addition, we were confirmed that the real-time embedding and detection from the streaming-based audio forensic marking system that has been implemented on the server/client is possible.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.1
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• pp.115-127
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• 2024

The recent increase in digital audio media has greatly expanded the size and diversity of sound data, which has increased the importance of sound data analysis in the digital forensics process. However, the lack of standardized procedures and guidelines for sound data analysis has caused problems with the consistency and reliability of analysis results. The digital environment includes a wide variety of audio formats and recording conditions, but current audio forensic methodologies do not adequately reflect this diversity. Therefore, this study identifies Life-Cycle-based sound data elemental technologies and provides overall guidelines for sound data analysis so that effective analysis can be performed in all situations. Furthermore, the identified elemental technologies were analyzed for use in the development of digital forensic techniques for sound data. To demonstrate the effectiveness of the life-cycle-based sound data elemental technology identification system presented in this study, a case study on the process of developing an emergency retrieval technology based on sound data is presented. Through this case study, we confirmed that the elemental technologies identified based on the Life-Cycle in the process of developing digital forensic technology for sound data ensure the quality and consistency of data analysis and enable efficient sound data analysis.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.2
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• pp.73-83
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• 2014

Thanks to the development of diverse audio editing Technology, audio file can be easily revised. As a result, diverse social problems like forgery may be caused. Digital forensic technology is actively studied to solve these problems. In this paper, a hand-held device identification method, an area of digital forensic technology is proposed. It uses the noise features of devices caused by the design and the integrated circuit of each device but cannot be identified by the audience. Wiener filter is used to get the noise sounds of devices and their acoustic features are extracted via MIRtoolbox and then they are trained by multi-layer neural network. To evaluate the proposed method, we use 5-fold cross-validation for the recorded data collected from 6 mobile devices. The experiments show the performance 99.9%. We also perform some experiments to observe the noise features of mobile devices are still useful after the data are uploaded to UCC. The experiments show the performance of 99.8% for UCC data.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.1103-1109
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• 2023

Today, as the number of audio files submitted as legal evidence increases with the proliferation of smartphones, the integrity of audio files has become an important issue. Accordingly, the purpose of this study is to explore whether the metadata and file structure of audio files recorded on Samsung smartphones can be manipulated to be identical to the original. This study was based on Samsung smartphones, the most widely used in Korea, and conducted experiments on the built-in voice recording app and the 'Easy Voice Recorder' app, which is the most popular recording app. Through the experiments of this study, it was proven that the metadata and file structure of audio files can be manipulated. Therefore, this study reveals that metadata and file structure analysis have limitations in proving the integrity when audio files are analyzed for adoption as legal evidence. They also argue for the need to develop new voice file forgery technology that does not rely on metadata and file structure analysis.

• Journal of KIISE
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• v.45 no.3
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• pp.311-320
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• 2018

Recently, the use of digital audio and video as proof in criminal and all kinds of litigation is increasing, and scientific investigation using digital forensic technique is developing. With the development of computing and file editing technologies, anyone can simply manipulate video files, and the number of cases of manipulating digital data is increasing. As a result, the integrity of the evidence and the reliability of the evidence Is required. In this paper, we propose a technique for extracting the Electrical Network Frequency (ENF) through a grid of power grids according to the geographical environment for power supply, and then performing signal processing for peak detection using QIFFT. Through the detection algorithm using the standard deviation, it was confirmed that the video file was falsified with 73% accuracy and the forgery point was found.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.807-812
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• 2022

Recently, as the number of voice recording files submitted as court evidence increases, the number of cases claiming forgery is also increasing. If the audio recording file structure and metadata, which are objective grounds, are completely forged, it is actually impossible to detect forgery of the sophisticated audio recording file. It is extremely rare for the court to reject the file structure and metadata analysis performed with the forged audio recording file. The purpose of this study is to prove that forgery of voice recording file structure and metadata is easily possible. To this end, in this study, it was introduced that forgery detection is impossible when the 'mixed paste' function, which enables sophisticated editing based on the typification of the editing method of voice recording files, is applied. Moreover, it has been proven through experiments that forgery of file structure and metadata is possible. Therefore, a stricter standard for judging the admissibility of evidence is required when the audio recording file is adopted as digital evidence. This study will not only contribute to the standard of integrity in the adoption of digital evidence by judges, but will also contribute to the method of constructing a dataset for artificial intelligence in detecting forgery of recorded files that is expected to be developed in the future.