A new fingerprinting scheme using social network analysis for majority attack

Abstract

Digital fingerprinting is a technology to protect multimedia content from unauthorized redistribution. However, collusion attack is a cost-efficient attack for digital fingerprinting, where groups of dishonest users create a pirate copy using their copies for the purpose of attenuating or removing the fingerprints. In this paper, FCBSN, Fingerprinting Code Based on Social Networks, for coding the user's fingerprints to resist majority attack, is proposed. The proposed scheme stems from the concept of coalition which always occurred in a social network. Different from all existing work, we explore the notion of the hierarchical community structure of social network and its intrinsic properties to assign fingerprints to users, drawing on the social relation according to the similar metric between two users. Theoretical analysis and experimental results show that the FCBSN detector outperforms the existing group detector for BS code and Tardos detector by large margins.