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Tytuł artykułu

Detection of Montage in Lossy Compressed Digital Audio Recordings

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Języki publikacji
EN
Abstrakty
EN
This paper addresses the problem of tampering detection and discusses methods used for authenticity analysis of digital audio recordings. Presented approach is based on frame offset measurement in audio files compressed and decoded by using perceptual audio coding algorithms which employ modified discrete cosine transform. The minimum values of total number of active MDCT coefficients occur for frame shifts equal to multiplications of applied window length. Any modification of audio file, including cutting off or pasting a part of audio recording causes a disturbance within this regularity. In this study the algorithm based on checking frame offset previously described in the literature is expanded by using each of four types of analysis windows commonly applied in the majority of MDCT based encoders. To enhance the robustness of the method additional histogram analysis is performed by detecting the presence of small value spectral components. Moreover, computation of maximum values of nonzero spectral coefficients is employed, which creates a gating function for the results obtained based on previous algorithm. This solution radically minimizes a number of false detections of forgeries. The influence of compression algorithms’ parameters on detection of forgeries is presented by applying AAC and Ogg Vorbis encoders as examples. The effectiveness of tampering detection algorithms proposed in this paper is tested on a predefined music database and compared graphically using ROC-like curves.
Rocznik
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65--72
Opis fizyczny
Bibliogr. 19 poz., tab., wykr.
Twórcy
autor
  • Institute of Radioelectronics, Warsaw University of Technology Nowowiejska 15/19, 00-665 Warszawa, Poland
Bibliografia
  • 1. ATTI V., PAINTER T., SPANIAS A. (2007), Audio Signal Processing and Coding, John Wiley & Sons, Inc., Hoboken, New Jersey.
  • 2. BRADLEY A.B., PRINCEN J.P. (1986), Analysis/synthesis filter bank design based on time domain aliasing cancellation'', IEEE Transactions on Acoustics, Speech and Signal Processing, 34, 5, 1153-1161.
  • 3. CHEN Y., HSU C. (2008), Image tampering detection by blocking periodicity analysis in JPEG compressed images, Proceedings of 10th Workshop on Multimedia Signal Processing, Oct. 8-10, pp. 803-808, Cairns, Queensland.
  • 4. DĄBROWSKI A., MARCINIAK T. (2008), Audio Signal Processing, [in:] Digital Systems and Applications Oklobdzija V.G. [Ed.], Chapter 11, CRC Press, Davis, USA.
  • 5. FARID H., WANG W. (2009), Exposing Digital Forgeries in Video by Detecting Double Quantization, Proceedings of ACM Multimedia and Security Workshop, Princeton.
  • 6. FULOP S.A. (2011), Speech Spectrum, Analysis, p. 32, Springer-Verlag, Berlin Heidelberg.
  • 7. GEIGER R., HERRE J. MOEHRS S. (2002), Analysing decompressed audio with the Inverse Decoder - towards an operative algorithm,, Proceedings of 112th AES Convention, May 10-13, Munich, Germany.
  • 8. GERADTS Z., HUIJBREGTSE M. (2009), Using the ENF criterion, for determining the ti.m.e of recording of short digital audio recordings, Proceedings of 3rd International Worshop on Computational Forensics, August 13-14, The Hague, The Netherlands.
  • 9. GRIGORAS C. (2007), Applications of ENF criterion in forensic audio, video, computer and telecommunication analysis, Forensic Science International, 167, 136-145.
  • 10. GRIGORAS C. (2010), Statistical Tools for Multimedia Forensics: Compression Effects Analysis, Proceedings of 39th AES International Conference Audio Forensics, June 17-19, Hillerod, Denmark.
  • 11. HERRE J., SCHUG M. (2000), Analysis of Decompressed Audio - The Inverse Decoder, Proceedings of 109th AES Convention, September 22-25, Los Angeles, USA.
  • 12. HUANG J., QU Z., YANG R. (2008), Detecting digital audio forgeries by checking frame offsets, Proceedings of 10th ACM workshop on Multimedia and security - International Multimedia Conference, pp. 21-26, Oxford.
  • 13. HUANG J., SHI Y.Q., YANG R. (2009), Defeating Fake- Quality MP3, Proceedings of 11th ACM workshop on Multimedia and security - International Multimedia Conference, Sep. 7-8, Princeton NJ.
  • 14. KORYCKI R. (2010), Methods of Time-Frequency Analysis in Authentication of Digital Audio Recordings, International Journal of Electronics and Telecommunications, 56, 257-262.
  • 15. KORYCKI R. (2011), Research, on Authentication of Compressed Audio Recordings, Proceedings of 14th International Symposium on Sound Engineering and Tonmeistering ISSET 2011, May 19-21, Wroclaw, Poland.
  • 16. KORYCKI R. (2012), Detection of tampering in lossy compressed digital audio recordings, Proceedings of Joint Conference New Trends in Audio and Video & Signal Processing: Algorithms, Architectures, Arrangements, and Applications NTAV/SPA 2012, September 27-29, Łódź, Poland, pp. 97-102.
  • 17. Liu Q., QIAO М., SUNG A.H. (2010), Detection, of double MP3 compression, Cognitive Computing, 2, 4, 291-296.
  • 18. MALVAR H.S. (1990), Lapped transforms for efficient transform./subband coding", IEEE Transactions on Acoustics, Speech and Signal Processing, 38, 6, 969- 978.
  • 19. Xiph.Org Foundation, Vorbis I specification, Feb. 2, 2012, p. 11, http://www.xiph.org/vorbis/doc/Vor- bisJ_spec.pdf
Typ dokumentu
Bibliografia
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bwmeta1.element.baztech-91cca310-624b-498e-94ad-b341091d03ac
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