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Conference Paper
Transaction Based Blockchain Profiling for Dark Web Cryptocurrency Forensics
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- Authors
- MinChang Kim, Mahdi Daghmehchi Firoozjaei, Hyoungshick Kim, Qing Tan
- Issue Date
- 2026-07
- Citation
- International Conference on Computers, Software, and Applications (COMPSAC) 2026, pp.1747-1748
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- Cryptocurrency transactions provide valuable forensic evidence for investigating illicit activity in dark web ecosystems. This fast abstract presents a transaction-centric blockchain profiling approach that characterizes suspicious behavior through transaction structure, temporal activity, and obfuscation-related indicators. We organize the proposed profiling features into three categories: transaction-level attributes, behavioral signatures, and obfuscation indicators. Using the Elliptic Bitcoin transaction graph dataset, we provide preliminary evidence that illicit transactions differ from licit activity in terms of amount regularity, fee behavior, and temporal burstiness. These findings suggest that transaction-based profiling can support cryptocurrency forensics when address attribution and off-chain intelligence are limited.
- Keyword
- Cryptocurrency Forensics, Blockchain Profiling, Dark Web Analysis, Transaction Graph Analysis, Illicit Trans action Detection
- KSP Keywords
- Dark web, Forensic Evidence, Graph analysis, Temporal activity, Web analysis, action detection, blockchain, graph dataset, transaction graph, transaction-based