Dual-Space Attacks against Random-Walk-based Anomaly Detection. (arXiv:2307.14387v1 [cs.CR])

Random Walks-based Anomaly Detection (RWAD) is commonly used to identify
anomalous patterns in various applications. An intriguing characteristic of
RWAD is that the input graph can either be pre-existing or constructed from raw
features. Consequently, there are two potential attack surfaces against RWAD:
graph-space attacks and feature-space attacks. In this paper, we explore this
vulnerability by designing practical dual-space attacks, investigating the
interplay between graph-space and feature-space attacks. To this end, we
conduct a thorough complexity analysis, proving that attacking …

anomaly detection applications attack attacks attack surfaces detection feature features identify input patterns random space