Behavior Forensics With Side Information for Multimedia Fingerprinting Social Networks
In multimedia social networks, there exists complicated dynamics among users who share and exchange multimedia content. Using multimedia fingerprinting as an example, this paper investigates the human behavior dynamics in the multimedia social networks with side information. Side information is the information other than the colluded multimedia content that can help increase the probability of detection. The authors study the impact of side information in multimedia fingerprinting and show that the statistical means of the detection statistics can help the fingerprint detector significantly improve the collusion resistance.