Estimation of Collusion Attack in Bias-based Binary Fingerprinting Code

Tatsuya Yasui, Minoru Kuribayashi, Nobuo Funabiki, Isao Echizen

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

Abstract

An optimal detector known as MAP detector has been proposed for the probabilistic fingerprinting codes such as Tardos and Nuida codes. However, it needs two kinds of important information. One is the collusion strategy which is used at the generation of a pirated codeword from colluders' codewords, and the other is the number of colluders. In this study, we propose an estimator which outputs these two parameters from a pirated codeword. At the estimation, we measure a bias in the pirated codeword by observing the number of symbols '0' and '1', and compare with possible bias patterns calculated from collusion strategies and number of colluders. As a result of computer simulation, it is confirmed that a collusion strategy and number of colluders can be estimated with high probability. In addition, it is revealed that the traceability of the detector using the proposed estimator is extremely close to the optimal detector.

Original languageEnglish
Title of host publication2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1550-1555
Number of pages6
ISBN (Electronic)9789881476852
DOIs
Publication statusPublished - Mar 4 2019
Event10th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Honolulu, United States
Duration: Nov 12 2018Nov 15 2018

Publication series

Name2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings

Conference

Conference10th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018
CountryUnited States
CityHonolulu
Period11/12/1811/15/18

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ASJC Scopus subject areas

  • Information Systems

Cite this

Yasui, T., Kuribayashi, M., Funabiki, N., & Echizen, I. (2019). Estimation of Collusion Attack in Bias-based Binary Fingerprinting Code. In 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings (pp. 1550-1555). [8659681] (2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/APSIPA.2018.8659681