Aluna WANG

Abstract

Anomaly detection is a critical tool for organizations and marketplaces looking to build trust and mitigate risks. In this tutorial, we will explore the key concepts and techniques involved in anomaly detection and demonstrate how they can be leveraged for high-stakes tasks such as communication surveillance, transaction monitoring, anti-money laundering, and insider trading detection. We will focus on the use of unsupervised machine learning and graph-based techniques, explaining why they are particularly effective for detecting anomalies when we face information constraints or data complexity. Through practical examples and hands-on experience, participants will gain a deeper understanding of how to design anomaly detection solutions for building trust in organizations and marketplaces and how to implement those solutions in real-world scenarios.