Abstract
TOPOS: Topological Profiling of On chain Subgraphs for Cross Chain Forensics
2026 IEEE International Conference on Blockchain and Cryptocurrency, pp.1-4
2026 IEEE International Conference on Blockchain and Cryptocurrency (ICBC) (Brisbane, Australia, 01/06/2026–05/06/2026)
01/06/2026
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Abstract
Cross-chain bridges have emerged as high-value targets, often serving as pseudo-anonymization layers that evade traditional behavioral heuristics. This paper presents TOPOS (TOpological Profiling of On-chain Subgraphs), a framework utilizing Heterogeneous Graph Networks (HGN) to identify malicious clusters through topological risk propagation. Evaluated against the 2024 Orbit Bridge exploit, TOPOS achieved a 100% detection rate of primary exploiters using only the bridge vault as a seed. While traditional heuristics assigned a mean risk score of only 0.134 to the attack cluster, TOPOS accurately identified 15 Critical and 28 High-risk entities with a mean score of 0.851. These results demonstrate that topological signals are superior to temporal behavior for characterizing the forensic blast radius of cross-chain exploits in real-time.
Details
- Title
- TOPOS: Topological Profiling of On chain Subgraphs for Cross Chain Forensics
- Creators
- Aravinda S. Rao - RNS Institute of Technology (India)Babu Pillai - Griffith University
- Publication Details
- 2026 IEEE International Conference on Blockchain and Cryptocurrency, pp.1-4
- Conference
- 2026 IEEE International Conference on Blockchain and Cryptocurrency (ICBC) (Brisbane, Australia, 01/06/2026–05/06/2026)
- Publisher
- IEEE
- Identifiers
- 9798331586331; 991013389951802368
- Academic Unit
- Faculty of Science and Engineering
- Language
- English
- Resource Type
- Abstract