Near-Optimal Detection for Binary Tardos Code by Estimating Collusion Strategy

Tatsuya Yasui, Minoru Kuribayashi, Nobuo Funabiki, Isao Echizen

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


A previously proposed optimal detector for biasbased fingerprinting codes such as Tardos and Nuida requires two kinds of important information: The number of colluders and the collusion strategy used to generate the pirated codeword. An estimator has now been derived for these two parameters. The bias in the pirated codeword is measured by observing the number of zeros and ones and compared with possible bias patterns calculated using information about the collusion strategy and number of colluders. Computer simulation demonstrated that the collusion strategy and number of colluders can be estimated with high probability and that the traceability of a detector using the proposed estimator is extremely close to being optimal.

Original languageEnglish
Article number8917678
Pages (from-to)2069-2080
Number of pages12
JournalIEEE Transactions on Information Forensics and Security
Publication statusPublished - 2020


  • Collusion strategy
  • Estimator
  • Fingerprinting code
  • Number of colluders
  • Optimal detector

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Computer Networks and Communications


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