2 papers
cs.LG2026
Quality over Quantity: Semi-Supervised Detection of Illicit Bitcoin Flows via Feature Engineering
Yekaterina Smolenkova, Nickolay Larionov, Nikolay Ivanov +1
Detecting illicit cryptocurrency transactions is hampered by extreme class imbalance, adversarial obfuscation, and a scarcity of reliable labels. While semi-supervised learning (SS…
cs.CR2026
Shedding Light on Complex Bitcoin Mixer Transactions: 67-Fold Reduction in Unclassified Cases
Nikolay Larionov, Yekaterina Smolenkova, Yury Yanovich
Bitcoin's Unspent Transaction Output (UTXO) model enables public analysis of fund flows, but users often merge transactions into Shared Send Mixers (SSMs) to obscure these flows. U…