FedAD-Bench: A Unified Benchmark for Federated Unsupervised Anomaly Detection in Tabular Data

• Main Authors: Anwar, Ahmed, Moser, Brian, Herurkar, Dayananda, Raue, Federico, Hegiste, Vinit, Legler, Tatjana, Dengel, Andreas
• Format: Journal Article
• Language: English
• Published: 08.08.2024
• Subjects: Computer Science - Artificial Intelligence; Computer Science - Learning

The emergence of federated learning (FL) presents a promising approach to leverage decentralized data while preserving privacy. Furthermore, the combination of FL and anomaly detection is particularly compelling because it allows for detecting rare and critical anomalies (usually also rare in locall...