Title
Universal Scoring Function Based On Bias Equalizer For Bias-Based Fingerprinting Codes
Abstract
The study of universal detector for fingerprinting code is strongly dependent on the design of scoring function. The optimal detector is known as MAP detector that calculates an optimal correlation score for a given single user's codeword. However, the knowledge about the number of colluders and their collusion strategy are inevitable. In this paper, we propose a new scoring function that equalizes the bias between symbols of codeword, which is called bias equalizer. We further investigate an efficient scoring function based on the bias equalizer under the relaxed marking assumption such that white Gaussian noise is added to a pirated codeword. The performance is compared with the MAP detector as well as some state-of-the-art scoring functions.
Year
DOI
Venue
2018
10.1587/transfun.E101.A.119
IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES
Keywords
Field
DocType
bias-based fingerprinting code, universal scoring function, relaxed marking assumption
Equalizer,Arithmetic,Theoretical computer science,Mathematics
Journal
Volume
Issue
ISSN
E101A
1
1745-1337
Citations 
PageRank 
References 
1
0.37
9
Authors
2
Name
Order
Citations
PageRank
Minoru Kuribayashi12319.55
Nobuo Funabiki222769.87