214 research outputs found
Saddle-point Solution of the Fingerprinting Capacity Game Under the Marking Assumption
We study a fingerprinting game in which the collusion channel is 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 maxmin games with mutual information as the payoff function.
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 and the fingerprint alphabet is binary,
we derive equations that can numerically solve the capacity game for arbitrary
. We also provide tight upper and lower bounds on the capacity. Finally, we
discuss the asymptotic behavior of the fingerprinting game for large and
practical implementation issues.Comment: 5 pages, to appear in 2009 IEEE International Symposium on
Information Theory (ISIT 2009), Seoul, Korea, June 200
On the Saddle-point Solution and the Large-Coalition Asymptotics 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 capacity decays quadratically with k. Furthermore, we prove
rigorously that the asymptotic capacity is 1/(k^2 2ln2) 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.Comment: submitted to IEEE Trans. on Information Forensics and Securit
Capacities and Capacity-Achieving Decoders for Various Fingerprinting Games
Combining an information-theoretic approach to fingerprinting with a more
constructive, statistical approach, we derive new results on the fingerprinting
capacities for various informed settings, as well as new log-likelihood
decoders with provable code lengths that asymptotically match these capacities.
The simple decoder built against the interleaving attack is further shown to
achieve the simple capacity for unknown attacks, and is argued to be an
improved version of the recently proposed decoder of Oosterwijk et al. With
this new universal decoder, cut-offs on the bias distribution function can
finally be dismissed.
Besides the application of these results to fingerprinting, a direct
consequence of our results to group testing is that (i) a simple decoder
asymptotically requires a factor 1.44 more tests to find defectives than a
joint decoder, and (ii) the simple decoder presented in this paper provably
achieves this bound.Comment: 13 pages, 2 figure
Asymptotics of Fingerprinting and Group Testing: Tight Bounds from Channel Capacities
In this work we consider the large-coalition asymptotics of various
fingerprinting and group testing games, and derive explicit expressions for the
capacities for each of these models. We do this both for simple decoders (fast
but suboptimal) and for joint decoders (slow but optimal).
For fingerprinting, we show that if the pirate strategy is known, the
capacity often decreases linearly with the number of colluders, instead of
quadratically as in the uninformed fingerprinting game. For many attacks the
joint capacity is further shown to be strictly higher than the simple capacity.
For group testing, we improve upon known results about the joint capacities,
and derive new explicit asymptotics for the simple capacities. These show that
existing simple group testing algorithms are suboptimal, and that simple
decoders cannot asymptotically be as efficient as joint decoders. For the
traditional group testing model, we show that the gap between the simple and
joint capacities is a factor 1.44 for large numbers of defectives.Comment: 14 pages, 6 figure
Towards joint decoding of binary Tardos fingerprinting codes
The class of joint decoder of probabilistic fingerprinting codes is of utmost
importance in theoretical papers to establish the concept of fingerprint
capacity. However, no implementation supporting a large user base is known to
date. This article presents an iterative decoder which is, as far as we are
aware of, the first practical attempt towards joint decoding. The
discriminative feature of the scores benefits on one hand from the
side-information of previously accused users, and on the other hand, from
recently introduced universal linear decoders for compound channels. Neither
the code construction nor the decoder make precise assumptions about the
collusion (size or strategy). The extension to incorporate soft outputs from
the watermarking layer is straightforward. An extensive experimental work
benchmarks the very good performance and offers a clear comparison with
previous state-of-the-art decoders.Comment: submitted to IEEE Trans. on Information Forensics and Security. -
typos corrected, one new plot, references added about ECC based
fingerprinting code
Asymptotically false-positive-maximizing attack on non-binary Tardos codes
We use a method recently introduced by Simone and Skoric to study accusation
probabilities for non-binary Tardos fingerprinting codes. We generalize the
pre-computation steps in this approach to include a broad class of collusion
attack strategies. We analytically derive properties of a special attack that
asymptotically maximizes false accusation probabilities. We present numerical
results on sufficient code lengths for this attack, and explain the abrupt
transitions that occur in these results
Asymptotics of Fingerprinting and Group Testing: Capacity-Achieving Log-Likelihood Decoders
We study the large-coalition asymptotics of fingerprinting and group testing,
and derive explicit decoders that provably achieve capacity for many of the
considered models. We do this both for simple decoders (fast but suboptimal)
and for joint decoders (slow but optimal), and both for informed and uninformed
settings.
For fingerprinting, we show that if the pirate strategy is known, the
Neyman-Pearson-based log-likelihood decoders provably achieve capacity,
regardless of the strategy. The decoder built against the interleaving attack
is further shown to be a universal decoder, able to deal with arbitrary attacks
and achieving the uninformed capacity. This universal decoder is shown to be
closely related to the Lagrange-optimized decoder of Oosterwijk et al. and the
empirical mutual information decoder of Moulin. Joint decoders are also
proposed, and we conjecture that these also achieve the corresponding joint
capacities.
For group testing, the simple decoder for the classical model is shown to be
more efficient than the one of Chan et al. and it provably achieves the simple
group testing capacity. For generalizations of this model such as noisy group
testing, the resulting simple decoders also achieve the corresponding simple
capacities.Comment: 14 pages, 2 figure
Optimal sequential fingerprinting: Wald vs. Tardos
We study sequential collusion-resistant fingerprinting, where the
fingerprinting code is generated in advance but accusations may be made between
rounds, and show that in this setting both the dynamic Tardos scheme and
schemes building upon Wald's sequential probability ratio test (SPRT) are
asymptotically optimal. We further compare these two approaches to sequential
fingerprinting, highlighting differences between the two schemes. Based on
these differences, we argue that Wald's scheme should in general be preferred
over the dynamic Tardos scheme, even though both schemes have their merits. As
a side result, we derive an optimal sequential group testing method for the
classical model, which can easily be generalized to different group testing
models.Comment: 12 pages, 10 figure
Worst case attacks against binary probabilistic traitor tracing codes
An insightful view into the design of traitor tracing codes should
necessarily consider the worst case attacks that the colluders can lead. This
paper takes an information-theoretic point of view where the worst case attack
is defined as the collusion strategy minimizing the achievable rate of the
traitor tracing code. Two different decoders are envisaged, the joint decoder
and the simple decoder, as recently defined by P. Moulin
\cite{Moulin08universal}. Several classes of colluders are defined with
increasing power. The worst case attack is derived for each class and each
decoder when applied to Tardos' codes and a probabilistic version of the
Boneh-Shaw construction. This contextual study gives the real rates achievable
by the binary probabilistic traitor tracing codes. Attacks usually considered
in literature, such as majority or minority votes, are indeed largely
suboptimal. This article also shows the utmost importance of the time-sharing
concept in a probabilistic codes.Comment: submitted to IEEE Trans. on Information Forensics and Securit
Efficient Probabilistic Group Testing Based on Traitor Tracing
Inspired by recent results from collusion-resistant traitor tracing, we
provide a framework for constructing efficient probabilistic group testing
schemes. In the traditional group testing model, our scheme asymptotically
requires T ~ 2 K ln N tests to find (with high probability) the correct set of
K defectives out of N items. The framework is also applied to several noisy
group testing and threshold group testing models, often leading to improvements
over previously known results, but we emphasize that this framework can be
applied to other variants of the classical model as well, both in adaptive and
in non-adaptive settings.Comment: 8 pages, 3 figures, 1 tabl
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