Darko Kirovski, Henrique S. Malvar, and Yacov Yacobi
We present a new dual watermarking and fingerprinting system, where initially all copies of a protected object are identically watermarked using a secret key, but individual detection keys are distinct. By knowing a detection key, an adversary cannot recreate the original content from the watermarked content. However, knowledge of any one detection key is sufficient for modifying the object so that a detector using that key would fail to detect the marks. Detectors using other detection keys would not be fooled, and such a modified object necessarily contains enough information about the broken detector key – the fingerprint. Our dual system limits the scope of possible attacks, when compared to classic fingerprinting systems. Under optimal attacks, the size of the collusion necessary to remove the marks without leaving a detectable fingerprint is superlinear in object size, whereas classic fingerprinting has a lower bound on collusion resistance that is approximately fourth root in object size. By using our scheme one can achieve collusion resistance of up to 900,000 users for a two hour high-definition video.
Received the ACM Multimedia 2002 best paper award.
|Published in||ACM Multimedia|
|Publisher||Association for Computing Machinery, Inc.|
Copyright © 2002 by the Association for Computing Machinery, Inc. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Publications Dept, ACM Inc., fax +1 (212) 869-0481, or email@example.com. The definitive version of this paper can be found at ACM’s Digital Library --http://www.acm.org/dl/.