On the Role of Similarity in Detecting Masquerading Files

arXiv:2402.11227v1 Announce Type: cross
Abstract: Similarity has been applied to a wide range of security applications, typically used in machine learning models. We examine the problem posed by masquerading samples; that is samples crafted by bad actors to be similar or near identical to legitimate samples. We find that these samples potentially create significant problems for machine learning solutions. The primary problem being that bad actors can circumvent machine learning solutions by using masquerading samples.
We then examine the interplay …

abstract actors applications arxiv cs.cr cs.lg files machine machine learning machine learning models near role samples security type