Publication Type

Journal Article

Version

publishedVersion

Publication Date

7-2025

Abstract

This article examines a collection of assumptions used in the current literature on node anomaly detection in a network. The examination raises the question: What are anomalies in a network? Our attempt to answer this question has provided some interesting findings and led to some open questions. This is the first article which formally defines anomalies in a network and introduces the concept of self-verifiability of a detector without ground-truths in a network. They enable existing detectors to be categorized into two types along the line whether they are self-verifiable or not. We suggest a method to evaluate self-verifiable detectors without ground-truths as an alternative to the existing evaluation method that relies on ground-truths.

Keywords

Anomaly detection, Network, Graph anomaly detection

Discipline

Artificial Intelligence and Robotics | OS and Networks

Research Areas

Intelligent Systems and Optimization

Areas of Excellence

Digital transformation

Publication

ACM Transactions on Knowledge Discovery from Data

Volume

19

Issue

6

First Page

1

Last Page

34

ISSN

1556-4681

Identifier

10.1145/3723007

Publisher

Association for Computing Machinery (ACM)

Additional URL

https://doi.org/10.1145/3723007

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