Anomaly Detection in Blockchain Networks: A Comprehensive Survey
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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 working over features of modern information and communication technologies (ICT). Peer-to-peer (P2) architecture of blockchain enhances these applications by providing strong security and trust-oriented guarantees, such as immutability, verifiability, and decentralization. Despite of these incredible features that blockchain technology brings to these ICT applications, modern research have indicated that these strong guarantees are not sufficient enough and blockchain networks may still prone to various security, privacy, and reliability related issues. In order to overcome these issues, it is important to identify the anomalous behaviour within time. Therefore, nowadays anomaly detection models are playing an important role in protection of modern blockchain networks. These anomaly detection models autonomously detect and predict anomaly in the network in order to protect network from unexpected attacks. In this article, we provide an in-depth survey regarding integration of anomaly detection models in blockchain technology. For this, we first discuss that how anomaly detection can aid in ensuring security of blockchain based applications. Then, we demonstrate certain fundamental evaluation matrices 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 perspective of each layer of blockchain to provide readers an in-depth overview of integration that has been carried out till date. Finally, we conclude the article by highlighting certain important challenges alongside discussing that how they can serve as a future research directions for new researchers in the field.
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