Benchmarking of scoring functions for bias-based fingerprinting code

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

3 Citations (Scopus)

Abstract

The study of universal detector for fingerprinting code is strongly dependent on the design of scoring function. The best detector is known as the MAP detector that calculates an optimal correlation score, but the number of colluders and their collusion strategy are inevitable. Although there are some scoring functions under some collusion strategies and asymptotic analyses, their numerical evaluation has not been done. In this study, their performance is evaluated for some typical collusion strategies using a discretized bias-based binary fingerprinting code. We also propose a simple but efficient scoring function based on a heuristic observation.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2039-2043
Number of pages5
Volume2016-May
ISBN (Electronic)9781479999880
DOIs
Publication statusPublished - May 18 2016
Event41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Shanghai, China
Duration: Mar 20 2016Mar 25 2016

Other

Other41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016
CountryChina
CityShanghai
Period3/20/163/25/16

Keywords

  • collusion attack
  • fingerprinting code
  • scoring function

ASJC Scopus subject areas

  • Signal Processing
  • Software
  • Electrical and Electronic Engineering

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  • Cite this

    Kuribayashi, M. (2016). Benchmarking of scoring functions for bias-based fingerprinting code. In 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings (Vol. 2016-May, pp. 2039-2043). [7472035] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2016.7472035