Topological Anomaly Detection in Dynamic Multilayer Blockchain Networks

• Published in: Machine Learning and Knowledge Discovery in Databases. Research Track Vol. 12975; pp. 788 - 804
• Main Authors: Ofori-Boateng, D., Dominguez, I. Segovia, Akcora, C., Kantarcioglu, M., Gel, Y. R.
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2021; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Anomaly detection; Blockchain transaction; Clique persistent homology; Dynamic multilayer network; Topological data analysis
• ISBN: 3030864855; 9783030864859
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-030-86486-6_48

Motivated by the recent surge of criminal activities with cross-cryptocurrency trades, we introduce a new topological perspective to structural anomaly detection in dynamic multilayer networks. We postulate that anomalies in the underlying blockchain transaction graph that are composed of multiple l...