BinarizedAttack: Structural Poisoning Attacks to Graph-based Anomaly Detection. (arXiv:2106.09989v5 [cs.LG] UPDATED)

Graph-based Anomaly Detection (GAD) is becoming prevalent due to the powerful
representation abilities of graphs as well as recent advances in graph mining
techniques. These GAD tools, however, expose a new attacking surface,
ironically due to their unique advantage of being able to exploit the relations
among data. That is, attackers now can manipulate those relations (i.e., the
structure of the graph) to allow some target nodes to evade detection. In this
paper, we exploit this vulnerability by designing a …

anomaly detection arxiv attacks detection graph graph-based