• DocumentCode
    3431788
  • Title

    Audio forensic authentication based on MOCC between ENF and reference signals

  • Author

    Zhisheng Lv ; Yongjian Hu ; Chang-Tsun Li ; Bei-bei Liu

  • Author_Institution
    Sch. of Electron. & Inf. Eng., South China Univ. of Technol., Guangzhou, China
  • fYear
    2013
  • fDate
    6-10 July 2013
  • Firstpage
    427
  • Lastpage
    431
  • Abstract
    This paper proposes a new audio authenticity detection algorithm based on the max offset for cross correlation (MOCC) between the extracted ENF (Electric Network Frequency) signal and the reference signal. We first extract the ENF signal from a query audio signal. And then we partition it into overlapping blocks for forgery detection. The MOCC between the extracted ENF and the reference signal is calculated block by block. We also introduce an enhancement scheme to improve the quality of the ENF signal before the calculation of the MOCC. Our proposed method can detect not only audio forgery but also the edited region and audio forgery type. The effectiveness of our method has been verified by experiments on digitally edited audio signals.
  • Keywords
    audio signal processing; digital forensics; message authentication; signal detection; ENF signal; MOCC; audio forensic authentication; authenticity detection algorithm; digitally edited audio signals; electric network frequency signal; enhancement scheme; forgery detection; max offset for cross correlation; query audio signal; reference signals; Correlation; Discrete Fourier transforms; Forensics; Forgery; Indexes; Noise; Electric network frequency; audio forgery detection; max offset for cross correlation; single-frequency reference signal;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal and Information Processing (ChinaSIP), 2013 IEEE China Summit & International Conference on
  • Conference_Location
    Beijing
  • Type

    conf

  • DOI
    10.1109/ChinaSIP.2013.6625375
  • Filename
    6625375