Collusion-aware traitor tracing in multimedia fingerprinting using sparse signal approximation

David Varodayan, Christine Pépin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We pose the problem of tracing traitors, who have colluded to circumvent a multimedia fingerprinting system, as a sparse underdeter-mined linear problem. We propose a range of detection algorithms, based on sparse signal approximation, that span a tradeoff between performance and complexity. These algorithms are superior to conventional detection by correlation because they are collusion-aware. The simplest algorithm among them is more expensive than correlation by only a constant factor, and the second simplest one is more expensive by only a factor linear in the maximum number of traitors. We demonstrate that our proposed algorithms extend the robustness of already deployed fingerprinting schemes under both linear and nonlinear collusion attacks. For example, roughly twice as many traitors can be traced reliably than by using correlation, under mean or median collusion followed by compression.

Original languageEnglish (US)
Title of host publication2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Pages1645-1648
Number of pages4
DOIs
StatePublished - 2008
Externally publishedYes
Event2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - Las Vegas, NV, United States
Duration: Mar 31 2008Apr 4 2008

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Country/TerritoryUnited States
CityLas Vegas, NV
Period3/31/084/4/08

Keywords

  • Digital watermarking
  • Multimedia fingerprinting
  • Sparse signal approximation
  • l-norm minimization

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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