On the saddle-point solution and the large-coalition behavior of fingerprinting games

We study a fingerprinting game in which the number of colluders and the collusion channel are unknown. The encoder embeds fingerprints into a host sequence and provides the decoder with the capability to trace back pirated copies to the colluders. Fingerprinting capacity has recently been derived as the limit value of a sequence of maximin games with mutual information as their payoff functions. However, these games generally do not admit saddle-point solutions and are very hard to solve numerically. Here under the so-called Boneh-Shaw marking assumption, we reformulate the capacity as the value of a single two-person zero-sum game, and show that it is achieved by a saddle-point solution. If the maximal coalition size is $k$ and the fingerprinting alphabet is binary, we show that the capacity is in \Theta(1/k²). Furthermore, we prove rigorously that the asymptotic capacity is 1/(k² 2 \ln2) and we confirm our earlier conjecture that Tardos' choice of the arcsine distribution asymptotically maximizes the mutual information payoff function while the interleaving attack minimizes it. Along with the asymptotic behavior, numerical solutions to the game for small $k$ are also presented.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2010

Author dc:creator

• Huang, Yen-Wei

Contributors dc:contributor

• Moulin, Pierre

• fingerprinting
• traitor tracing
• capacity
• game theory
• minimax theorem
• Jeffreys' prior
• saddle-point problems

Statement dc:rights

• Copyright 2010 Yen-Wei Huang

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/16836

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/16836