Friends or Foes: Detecting Dishonest Recommenders in Online Social Networks
Viral marketing is becoming important due to the popularity of Online Social Networks (OSNs) and the fact that many users have integrated OSNs into their daily activities, e.g., they provide recommendations to their friends on the products they purchased, or they make decision based on received recommendations. Nevertheless, this also opens door for "Shill attack": dishonest users may give wrong recommendations so as to distort the normal sales distribution. In this paper, the authors propose a detection mechanism to discover these dishonest users in OSNs. In particular, they present two fully distributed algorithms to detect attackers in both the baseline shill attack and the intelligent shill attack.