• DocumentCode
    3269217
  • Title

    On the systematic generation of Tardos’s fingerprinting codes

  • Author

    Kuribayashi, Minoru ; Akashi, Naoyuki ; Morii, Masakatu

  • Author_Institution
    Grad. Sch. of Eng., Kobe Univ., Kobe
  • fYear
    2008
  • fDate
    8-10 Oct. 2008
  • Firstpage
    748
  • Lastpage
    753
  • Abstract
    Digital fingerprinting is used to trace back illegal users, where unique ID known as digital fingerprints is embedded into a content before distribution. On the generation of such fingerprints, one of the important properties is collusion-resistance. Binary codes for fingerprinting with a code length of theoretically minimum order were proposed by Tardos, and the related works mainly focused on the reduction of the code length were presented. In this paper, we present a concrete and systematic construction of the Tardospsilas fingerprinting code using a chaotic map. Using a statistical model for correlation scores, a proper threshold for detecting colluders is calculated. Furthermore, for the reduction of computational costs required for the detection, a hierarchical structure is introduced on the codewords. The collusion-resistance of the generated fingerprinting codes is evaluated by a computer simulation.
  • Keywords
    binary codes; correlation methods; fingerprint identification; image coding; security of data; statistical analysis; Tardos digital fingerprinting codes; binary codes; chaotic map; colluder detection; collusion-resistance property; correlation scores; statistical model; Binary codes; Chaos; Computational efficiency; Computer simulation; Concrete; Detectors; Error probability; Fingerprint recognition; Logistics; Probability distribution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia Signal Processing, 2008 IEEE 10th Workshop on
  • Conference_Location
    Cairns, Qld
  • Print_ISBN
    978-1-4244-2294-4
  • Electronic_ISBN
    978-1-4244-2295-1
  • Type

    conf

  • DOI
    10.1109/MMSP.2008.4665174
  • Filename
    4665174