Imagine a shield against hidden dangers in cryptocurrency transaction
As a result of an internship project, Helen Miller (Pawsey intern), under the supervision of Dr MD REDOWAN MAHMUD & Dr sajib mistry from the School of EECMS and HPIS (High-Performance Intelligent Systems) Lab at Curtin University, in association with A/Prof Aneesh Krishna and Dr Mahbuba Afrin developed a cutting-edge system that analyzes relationships between addresses, transactions, and smart contracts.
Here’s the magic:
Knowledge Graph: The researchers built a graph representing relationships between addresses, transactions, and smart contracts on the Ethereum blockchain. Machine Learning on the Graph: They then used a machine learning technique called “collaborative filtering” to identify potential victims based on similarities with past targets.
Early Detection:
This approach allows for early detection and prevention of fraudulent activities, protecting users and their funds. This research paves the way for a more secure future for cryptocurrency transactions. By harnessing the power of Pawsey supercomputer, Machine Learning (ML), and graph technology, a safer environment for users can be created. Want to learn more?
Check out the full paper https://bit.ly/3S0sGKf
Project Leader.
