Traceable Content Distribution Using Wavelet Decomposition and Social Network Analysis

This paper identifies a novel secure content distribution framework based on wavelet decomposition and social network. The motivation is to facilitate trace illegally distributed content by using mapping between hierarchical community of social network and wavelet tree. Firstly, the host signal is encrypted, then the encrypted contents are delivered to users according to social network analysis, at last, the contents are fingerprinted with decryption on the receiving side to get many different copies. Fingerprints which are constructed with social network analysis are embedded in wavelet domain. The use of fingerprinting along with encryption can provide a double-layer of protection to digital media. Theory analysis proves that the proposed framework has significantly better performance than traditional content distribution mode. Experimental results prove that the proposed technique is not only resilient to collusion attacks, but also consume much less CPU time to trace colluders.