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Cited by 259

The DOI matches its Crossref record; 97 of the 97 references it cites were found in a registry or an index.

Anomaly Detection in Blockchain Networks: A Comprehensive Survey

Ul Hassan, Muneeb, Rehmani, Mubashir Husain, Chen, Jinjun·2023·IEEE Communications Surveys & Tutorials

Abstract

Over the past decade, blockchain technology has attracted a huge attention from both industry and academia because it can be integrated with a large number of everyday applications of modern information and communication technologies (ICT). Peer-to-peer (P2P) architecture of blockchain enhances these applications by providing strong security and trust-oriented guarantees, such as immutability, verifiability, and decentralization. Despite these incredible features that blockchain technology brings to these ICT applications, recent research has indicated that the strong guarantees are not sufficient enough and blockchain networks may still be prone to various security, privacy, and reliability issues. In order to overcome these issues, it is important to identify the anomalous behaviour within the actionable time frame. In this article, we provide an in-depth survey regarding integration of anomaly detection models in blockchain technology. For this, we first discuss how anomaly detection can aid in ensuring security of blockchain based applications. Then, we demonstrate certain fundamental evaluation metrics and key requirements that can play a critical role while developing anomaly detection models for blockchain. Afterwards, we present a thorough survey of various anomaly detection models from the perspective of each layer of blockchain. Finally, we conclude the article by highlighting certain important challenges alongside discussing how they can serve as future research directions for new researchers in the field.

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Metadata

Authors
Ul Hassan, M., Rehmani, M. H., & Chen, J.
Venue
IEEE Communications Surveys & Tutorials
Published
2023
Volume
25
Issue
1
Pages
289-318
ISSN
  • 1553-877X (ISSN-L)
  • 2373-745X
OpenAlex
W4200629745
Cited by
259
References
97
FWCI
54.48
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Anomaly Detection in Blockchain Networks: A Comprehensive Survey. https://app.cochat.ai/papers/10.1109/comst.2022.3205643
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Ul Hassan, M., Rehmani, M. H., & Chen, J. (2023). Anomaly Detection in Blockchain Networks: A Comprehensive Survey. IEEE Communications Surveys & Tutorials. https://doi.org/10.1109/comst.2022.3205643

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