CENSor: Detecting Illicit Bitcoin Operation via GCN-Based Hyperedge Classification
Cryptocurrencies have increasingly been used as a medium for illicit financial activities by criminals. Annually, billions of dollars’ worth of Bitcoin penetrate cryptocurrency exchanges. Despite the critical need for advanced Bitcoin financial forensics to investigate these criminal acti...
Saved in:
| Main Authors: | Suyeol Lee, Jaehan Kim, Minjae Seo, Seung Ho Na, Seungwon Shin, Jinwoo Kim |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10689425/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Sampling nodes and hyperedges via random walks on large hypergraphs
by: Kazuki Nakajima, et al.
Published: (2025-06-01) -
Clustering coefficient reflecting pairwise relationships within hyperedges
by: Rikuya Miyashita, et al.
Published: (2025-07-01) -
gShock: A GNN-Based Fingerprinting System for Permissioned Blockchain Networks Over Encrypted Channels
by: Minjae Seo, et al.
Published: (2024-01-01) -
Directed n-Superhypergraphs Incorporating Bipolar Fuzzy Information: A Multi-Tier Framework for Modeling Bipolar Uncertainty in Complex Networks
by: Florentin Smarandache, et al.
Published: (2025-07-01) -
Graph convolution network for fraud detection in bitcoin transactions
by: Ahmad Asiri, et al.
Published: (2025-04-01)