Deep Learning Approaches for Enhancing Security in Blockchain Systems: A Comprehensive Review and Analysis

Autores/as

  • D Vikram Department of Computer Science and Engineering, Dr. Mahalingam College of Engineering and Technology, Pollachi, India - 642003
  • S. Nagarajan Department of Computer Science and Engineering, Dr. Mahalingam College of Engineering and Technology, Pollachi, India - 642003
  • S. Kirubakaran Department of Computer Science and Engineering, Dr. Mahalingam College of Engineering and Technology, Pollachi, India - 642003
  • S. P. Santhoshkumar Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi, Chennai, Tamilnadu, India – 600062

DOI:

https://doi.org/10.5935/jetia.v12i61.4120

Resumen

Blockchain technology has drawn a lot of interest since it has the ability to completely transform a number of different industries by offering transparent and safe transactional platforms. However, as blockchain technology becomes more widely used, security breaches become more likely. In blockchain systems, advanced threats are typically difficult to identify and counter using conventional security methods. Deep learning methods have been a viable approach for improving blockchain network security in recent years. An extensive evaluation of deep learning techniques for identifying security breaches in blockchain systems is provided in this study. We classify these methods according to the kinds of security breaches they tackle and the particular deep learning models they use. In addition, we go over difficulties, unanswered research problems, and potential paths for applying deep learning to blockchain security

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Publicado

2026-10-19

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Articles

Cómo citar

Deep Learning Approaches for Enhancing Security in Blockchain Systems: A Comprehensive Review and Analysis. (2026). ITEGAM-JETIA, 12(61), 1275-1282. https://doi.org/10.5935/jetia.v12i61.4120