DocumentCode :
967750
Title :
Watermill: An Optimized Fingerprinting System for Databases under Constraints
Author :
Lafaye, Julien ; Gross-Amblard, David ; Constantin, Camelia ; Guerrouani, Meryem
Author_Institution :
Lab. Cedric, Paris
Volume :
20
Issue :
4
fYear :
2008
fDate :
4/1/2008 12:00:00 AM
Firstpage :
532
Lastpage :
546
Abstract :
This paper presents a walermarking/fingerprinting system for relational databases. It features a built-in declarative language to specify usability constraints that watermarked data sets must comply with. For a subset of these constraints, namely, weight-independent constraints, we propose a novel watermarking strategy that consists of translating them into an integer linear program. We show two watermarking strategies: an exhaustive one based on integer linear programming constraint solving and a scalable pairing heuristic. Fingerprinting applications, for which several distinct watermarks need to be computed, benefit from the reduced computation time of our method that precomputes the watermarks only once. Moreover, we show that our method enables practical collusion-secure fingerprinting since the precomputed watermarks are based on binary alterations located at exactly the same positions. The paper includes an in-depth analysis of false-hit and false-miss occurrence probabilities for the detection algorithm. Experiments performed on our open source software WATERMILL assess the watermark robustness against common attacks and show that our method outperforms the existing ones concerning the watermark embedding speed.
Keywords :
fingerprint identification; integer programming; linear programming; public domain software; relational databases; watermarking; Watermill; binary alterations; declarative language; fingerprinting system; integer linear programming; open source software; relational databases; watermarking system; weight-independent constraints; Security and Privacy Protection; database fingerprinting; database watermarking; optimization;
fLanguage :
English
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1041-4347
Type :
jour
DOI :
10.1109/TKDE.2007.190713
Filename :
4378379
Link To Document :
بازگشت