Abstract
The purchasing of customer databases, which is becoming more and more common, has led to a big problem: illegal distribution of purchased databases. An essential tool for identifying distributors is database fingerprinting. There are two basic problem in fingerprinting database: designing the fingerprint and embedding it. For the first problem, we have proven that Non-Adaptive Group Testing, which is used to identify specific items in a large population, can be used for fingerprinting and that it is secure against collusion attack efficiently. For the second problem, we have developed a solution that supports up to 262,144 fingerprints for 4,032 attributes, and that is secure against three types of attacks: attribute, collusion and complimentary. Moreover, illegal distributor can be identified within 0.15 seconds.
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Bui, T.V., Nguyen, B.Q., Nguyen, T.D., Sonehara, N., Echizen, I. (2013). Robust Fingerprinting Codes for Database. In: Aversa, R., Kołodziej, J., Zhang, J., Amato, F., Fortino, G. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2013. Lecture Notes in Computer Science, vol 8286. Springer, Cham. https://doi.org/10.1007/978-3-319-03889-6_19
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DOI: https://doi.org/10.1007/978-3-319-03889-6_19
Publisher Name: Springer, Cham
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