Uncovering Strong Ties: A Study of Indirect Sybil Attack on Signed Social Network

Yu Bu, Yulin Zhu, Longling Geng, Kai Zhou

Abstract: The Fairness and Goodness Algorithm (FGA) is a widely used trust system in signed directed networks. However, attackers can manipulate trust scores on FGA by launching indirect Sybil attacks and exploiting strong ties. In this work, we propose a novel attack method vicinage-attack that formulates the problem as a combination optimization problem for mining candidate attacking edges. Our method constructs perturbation spaces and infers the existence of polymorphic strong ties. To evaluate vicinage-attack, we compare it against several baselines and show the vicinage-attack outperforms them. Overall, our work highlights the potential dangers of indirect Sybil attacks on FGA and offers insight for detecting and mitigating these attacks.