A New Soft Decision Tracing Algorithm for Binary Fingerprinting Codes

  • Minoru Kuribayashi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7038)

Abstract

The performance of fingerprinting codes has been studied under the well-known marking assumption. In a realistic environment, however, a pirated copy will be distorted by an additional attack. Under the assumption that the distortion is modeled as AWGN, a soft decision method for a tracing algorithm has been proposed and the traceability has been experimentally evaluated. However, the previous soft decision method works directly with a received signal without considering the communication theory. In this study, we calculate the likelihood of received signal considering a posterior probability, and propose a soft decision tracing algorithm considering the characteristic of Gaussian channel. For the estimation of channel, we employ the expectation-maximization algorithm by giving constraints under the possible collusion strategies. We also propose an equalizer to give a proper weighting parameter for calculating a correlation score.

Keywords

Central Limit Theorem Gaussian Mixture Model Correlation Score Hard Decision Gaussian Channel 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Minoru Kuribayashi
    • 1
  1. 1.Graduate School of EngineeringKobe UniversityKobeJapan

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