3 accepted papers
Accurate graph annotation typically requires substantial labeled data, which is often challenging and resource-intensive to obtain. In this paper, we present Crowdsourced Homophily Ties Based Graph Annotation via Large Language Model (CSA-LLM), a novel approach that combines the strengths of crowdso…
Graph Neural Networks (GNNs) have become widely used in the field of graph mining. However, these networks are vulnerable to structural perturbations. While many research efforts have focused on analyzing vulnerability through poisoning attacks, we have identified an inefficiency in current attack l…
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 th…