User Tools

Site Tools


10a.006.UL - Application-Domain-Agnostic Anomaly Detection in Blockchain Transaction Graphs

Project - Summary


  • Blockchain technologies are prone to several types of misuses (e.g., money laundering and illegal marketplaces in Bitcoin) or mistakes (e.g., accident errors in blockchain-based healthcare management systems).
  • In this project, we develop a novel, sliding blocks approach to detect, visualize and monitor legitimate transactions in blockchain graphs that collectively pose anomalous behaviors due to misuses or mistakes.

Project - Team

Team Member Role Email Phone Number Academic Site/IAB
Mehmet Engin Tozal PI (337) 482 6604 UL Lafayette
Somtoo Chuckwu Student TBA UL Lafayette

Project - Novelty of Approach

Anomaly detection in blockchain graphs require new approaches because of their intrinsic features:

  • Large graph size
  • Disallowed node deletions
  • Frequent node/edge additions
  • Shorter anomaly spans
  • Varying anomaly patterns

The proposed approach is novel in terms of both exploiting the subgraph embedding through RPCA and lower memory and computational requirements to support agile anomaly detection and visualization under frequent graph updates.

Project - Deliverables

1 Develop a user-friendly visualization to allow users to explore anomalous subgraphs further
2 Develop the proposed anomaly detection approach and explore others
3 Fine tune the parameters of RPCA and sliding window size to improve the overall performance

Project - Benefits to IAB

Blockchain technologies have use cases beyond cryto-currencies:

  • MediLedger (Healthcare)
  • Dentacoin (Healthcare)
  • SmartLog (IoT, Logistics)
  • Smart Cities/Homes (IoT, Cybersecurity)
  • Circle (Finance)

IBM, JPMorgan and Softbank are among the large companies that have actively been investing in blockchain technologies.

We believe that the proposed project will complement current and future in-house, blockchain-based applications development efforts put by the IAB members.

Project - Documents

projects/year10/10a.006.ul.txt · Last modified: 2022/05/10 15:45 by sally.johnson