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his paper presents a watermarking/fingerprinting system for relational databases. It features a built-in declarative language to specify usability constraints that watermarked datasets must comply with. For a subset of these constraints, namely weight-independent constraints, we propose a novel watermarking strategy which 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 hits and false misses 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.
Security and Privacy Protection, optimization, database watermarking, database fingerprinting

C. Constantin, J. Lafaye, D. Gross-Amblard and M. Guerrouani, "Watermill: An Optimized Fingerprinting System for Databases under Constraints," in IEEE Transactions on Knowledge & Data Engineering, vol. 20, no. , pp. 532-546, 2007.
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