Anomaly and Fraud Detection in Blockchain Networks
Details
- Authors: Tudor Nechiti
- Title: Anomaly and Fraud Detection in Blockchain Networks
- Supervisor: Prof. Dr. Jörg Osterrieder
- Degree: Bachelor of Science
- University: University of Twente
- Year: 2023
- Status: Working Paper
Summary
Abstract
Blockchain-based systems gradually become more popular in these past years due to their characteristics of decentralization, consistency, anonymity and auditability. However, as it is the case with any technology, fraudulent actions can be conceived, albeit their success is significantly diminished in blockchain networks, due to their unique attributes. As a consequence, these make the detection of anomaly and fraud way more difficult than in a conventional network. We will investigate anomaly and fraud detection from the perspective of blockchain-based networks. Our proposed research aims to advance the understanding of the origins and behaviors of anomalies and fraud in these type of networks. Moreover, we aim to develop new, improved methods for static and dynamic anomaly detection that can be integrated with blockchain-based systems for real-time fraud detection