Universal Threshold Calculation for Fingerprinting Decoders using Mixture Models
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Universal Threshold Calculation for Fingerprinting Decoders using Mixture Models. / Schäfer, Marcel; Mair, Sebastian; Berchtold, Waldemar et al.
Proceedings of the 3rd ACM Workshop on Information Hiding and Multimedia Security. Association for Computing Machinery, Inc, 2015. S. 109-114 (IH and MMSec 2015 - Proceedings of the 2015 ACM Workshop on Information Hiding and Multimedia Security).Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
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}
RIS
TY - CHAP
T1 - Universal Threshold Calculation for Fingerprinting Decoders using Mixture Models
AU - Schäfer, Marcel
AU - Mair, Sebastian
AU - Berchtold, Waldemar
AU - Steinebach, Martin
N1 - Conference code: 3
PY - 2015/6/17
Y1 - 2015/6/17
N2 - Collusion attacks on watermarked media copies are commonly countered by probabilistically generated fingerprinting codes and appropriate tracing algorithms. The latter calculates accusation scores representing the suspiciousness of the fingerprints. In a 'detect many' scenario a threshold decides which scores are associated to the colluders. This work proposes a universal method to calculate thresholds for different decoders solely with knowledge of the accusation scores from the actual attack. Applying mixture models on the scores, the threshold is set up satisfying the selected error probabilities. It is independent from the fingerprint generation and can be applied at any decoder. Also no knowledge about the number of attackers or their strategy is needed.
AB - Collusion attacks on watermarked media copies are commonly countered by probabilistically generated fingerprinting codes and appropriate tracing algorithms. The latter calculates accusation scores representing the suspiciousness of the fingerprints. In a 'detect many' scenario a threshold decides which scores are associated to the colluders. This work proposes a universal method to calculate thresholds for different decoders solely with knowledge of the accusation scores from the actual attack. Applying mixture models on the scores, the threshold is set up satisfying the selected error probabilities. It is independent from the fingerprint generation and can be applied at any decoder. Also no knowledge about the number of attackers or their strategy is needed.
KW - Informatics
KW - Collusion attacks
KW - Digital watermarking
KW - Fingerprinting codes
KW - Mixture models
KW - Traitor tracing
UR - http://www.scopus.com/inward/record.url?scp=84962863575&partnerID=8YFLogxK
U2 - 10.1145/2756601.2756611
DO - 10.1145/2756601.2756611
M3 - Article in conference proceedings
SN - 978-1-4503-3587-4
T3 - IH and MMSec 2015 - Proceedings of the 2015 ACM Workshop on Information Hiding and Multimedia Security
SP - 109
EP - 114
BT - Proceedings of the 3rd ACM Workshop on Information Hiding and Multimedia Security
PB - Association for Computing Machinery, Inc
T2 - ACM Workshop on Information Hiding and Multimedia Security - 2015
Y2 - 17 June 2015 through 19 June 2015
ER -