Robust fingerprinting codes for database using non-adaptive group testing
by Thach V. Bui; Binh Q. Nguyen; Thuc D. Nguyen; Noboru Sonehara; Isao Echizen
International Journal of Big Data Intelligence (IJBDI), Vol. 2, No. 2, 2015

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.

Online publication date: Sat, 09-May-2015

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