A method to detect AAC audio forgery

Qingzhong Liu, Andrew H. Sung, Lei Chen, Ming Yang, Yanxin Liu, Zhongxue Chen, Jing Zhang

Research output: Contribution to book or proceedingConference articlepeer-review

1 Scopus citations

Abstract

Advanced Audio Coding (AAC), a standardized lossy compression scheme for digital audio, which was designed to be the successor of the MP3 format, generally achieves better sound quality than MP3 at similar bit rates. While AAC is also the default or standard audio format for many devices and AAC audio files may be presented as important digital evidences, the authentication of the audio files is highly needed but relatively missing. In this paper, we propose a scheme to expose tampered AAC audio streams that are encoded at the same encoding bit-rate. Specifically, we design a shift-recompression based method to retrieve the differential features between the re-encoded audio stream at each shifting and original audio stream, learning classifier is employed to recognize different patterns of differential features of the doctored forgery files and original (untouched) audio files. Experimental results show that our approach is very promising and effective to detect the forgery of the same encoding bit-rate on AAC audio streams. Our study also shows that shift recompression-based differential analysis is very effective for detection of the MP3 forgery at the same bit rate.
Original languageEnglish
Title of host publicationMOBIMEDIA 2015 - 8th International Conference on Mobile Multimedia Communications
EditorsXiao Wu, Min Chen, Honggang Wang
PublisherICST
ISBN (Electronic)9781631900662
DOIs
StatePublished - Aug 3 2015
Event8th International Conference on Mobile Multimedia Communications, MOBIMEDIA 2015 - Chengdu, China
Duration: May 25 2015May 27 2015

Publication series

NameMOBIMEDIA 2015 - 8th International Conference on Mobile Multimedia Communications

Conference

Conference8th International Conference on Mobile Multimedia Communications, MOBIMEDIA 2015
Country/TerritoryChina
CityChengdu
Period05/25/1505/27/15

Keywords

  • AAC
  • Audio forensics
  • Forgery detection
  • Same bitrate

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