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Anomaly Detection in Blockchain Using Machine Learning

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Computational Intelligence for Engineering and Management Applications

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 984))

Abstract

With the increasing use of Blockchain, community has become increasingly worried about its security, that has led to substantial research by academics, with anomaly detection being a major issue. Regardless of the fact that they can provide availability and integrity, the bulk of public Blockchain systems are decentralized and have minimal confidentiality. The Blockchain network is vulnerable to transaction privacy breaches since all of the network's keys are exposed to everyone. Various security flaws in Ethereum and smart contracts have recently been discovered. As a result, it's critical to improve Blockchain’s security features. This research will mainly use the literature survey method and the inductive analysis method to analyze the relevant research works for anomaly detection in Blockchain technology and to find out the trends and characteristics of the development and application of the anomaly detection models and explore its feasibility in ensuring security in Blockchain technology. This paper also proposes a framework for anomaly detection in Blockchain technology.

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Author information

Authors and Affiliations

  1. City University, 46100, Petaling Jaya, Malaysia

    Gulab Sanjay Rai & S. B. Goyal

  2. Department of Mechanical Engineering, MCKV Institute of Engineering, Howrah, West Bengal, India

    Prasenjit Chatterjee

Authors
  1. Gulab Sanjay Rai
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  2. S. B. Goyal
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  3. Prasenjit Chatterjee
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Corresponding author

Correspondence to S. B. Goyal .

Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering, MCKV Institute of Engineering, Howrah, West Bengal, India

    Prasenjit Chatterjee

  2. Department of Operations Research and Statistics, Faculty of Organizational Sciences, University of Belgrade, Belgrade, Serbia

    Dragan Pamucar

  3. Universidad Internacional de Valencia, Valencia, Spain

    Morteza Yazdani

  4. Department of Mechanical Engineering, National Institute of Technology Kurukshetra, Kurukshetra, Haryana, India

    Dilbagh Panchal

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Sanjay Rai, G., Goyal, S.B., Chatterjee, P. (2023). Anomaly Detection in Blockchain Using Machine Learning. In: Chatterjee, P., Pamucar, D., Yazdani, M., Panchal, D. (eds) Computational Intelligence for Engineering and Management Applications. Lecture Notes in Electrical Engineering, vol 984. Springer, Singapore. https://doi.org/10.1007/978-981-19-8493-8_37

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