Towards joint decoding of binary Tardos fingerprinting codes

Computer Science – Information Theory

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

submitted to IEEE Trans. on Information Forensics and Security. - typos corrected, one new plot, references added about ECC ba

Scientific paper

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.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Towards joint decoding of binary Tardos fingerprinting codes does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Towards joint decoding of binary Tardos fingerprinting codes, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Towards joint decoding of binary Tardos fingerprinting codes will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-17593

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.