Robust random cut forest based anomaly detection on streams

Code

• github.com/aws/random-cut-forest-by-aws
  none★ 235
• github.com/navdeep-g/robust-random-cut-forest
  none★ 0
• github.com/kLabUM/rrcf
  none★ 0

Abstract

In this paper we focus on the anomaly detection problem for dynamic data streams through the lens of random cut forests. We investigate a robust random cut data structure that can be used as a sketch or synopsis of the input stream. We provide a plausible definition of non-parametric anomalies based on the influence of an unseen point on the remainder of the data, i.e., the exter-nality imposed by that point. We show how the sketch can be efficiently updated in a dynamic data stream. We demonstrate the viability of the algorithm on publicly available real data.

Tasks

Reproductions