Abstract
Blockchain technology’s increasing adoption across diverse sectors necessitates robust security measures to mitigate rising fraudulent activities. This paper presents a comprehensive bibliometric analysis of anomaly detection research in blockchain networks from 2017 to 2024, conducted under the PRISMA paradigm. Using CiteSpace 6.4.R1, we systematically map the knowledge domain based on 363 WoSCC-indexed articles. The analysis encompasses collaboration networks, co-citation patterns, citation bursts, and keyword trends to identify emerging research directions, influential contributors, and persistent challenges. The study reveals geographical concentrations of research activity, key institutional players, the evolution of theoretical frameworks, and shifts from basic security mechanisms to sophisticated machine learning and graph neural network approaches. This research summarizes the state of the field and highlights future directions essential for blockchain security.
| Original language | English |
|---|---|
| Article number | 8330 |
| Number of pages | 28 |
| Journal | Applied Sciences |
| Volume | 15 |
| Issue number | 15 |
| DOIs | |
| Publication status | Published - 26 Jul 2025 |
Bibliographical note
Copyright © 2025 by the authors. Licensee MDPI, Basel, Switzerland.This article is an open access article distributed under the terms and
conditions of the Creative Commons Attribution (CC BY) license
(https://creativecommons.org/licenses/by/4.0/).
Keywords
- Blockchain
- Anomaly Detection
- domaine map analysis
- scientometric database
- Trends
- Knowledge graph
- CiteSpace