Live Video Forensics: Source Identification in Lossy Wireless Networks. Chen, S, Pande, A, Zeng, K, & Mohapatra, P IEEE Transactions on Information Forensics and Security, to appear.
abstract   bibtex   
Video source identification is very important in validating video evidence, tracking down video piracy crimes and regulating individual video sources. With the prevalence of wireless communication, wireless video cameras continue to replace their wired counterparts in security / surveillance systems and tactical networks. However, wirelessly streamed videos usually suffer from blocking and blurring due to inevitable packet loss in wireless transmissions. The existing source identification methods experience significant performance degradation or even fail to work when identifying videos with blocking and blurring. In this paper, we propose a method which is effective and efficient in identifying such wirelessly streamed videos. In addition, we also propose to incorporate wireless channel signatures and selective frame processing into source identification, which significantly improve the identification speed.
@article{ chenvideoTIFS,
  journal = {IEEE Transactions on Information Forensics and Security},
  author = {S Chen and  A Pande and K Zeng and P Mohapatra},
  title = { Live Video Forensics: Source Identification in Lossy Wireless Networks },
  year = {to appear},
  pages = {215-219},
  abstract = {Video source identification is very important in validating video evidence, 
tracking down video piracy crimes and regulating individual video sources. With the prevalence of wireless communication, 
wireless video cameras continue to replace their wired counterparts in security / surveillance systems and tactical networks.
 However, wirelessly streamed videos usually suffer from blocking and blurring due to inevitable packet loss in wireless
 transmissions. The existing source identification methods experience significant performance degradation or even fail to work 
when identifying videos with blocking and blurring. In this paper, we propose a method which is effective and efficient 
in identifying such wirelessly streamed videos. In addition, we also propose to incorporate wireless channel signatures
 and selective frame processing into source identification, which significantly improve the identification speed.},
  keywords = {SecurityPrivacyandTrust,WirelessNetworks}
}

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