A Framework for Learning-Based Attack Detection and Regulatory Compliance in Blockchain Technology

  • Olanrewaju Sanda

Student thesis: Doctoral Thesis


Blockchain technology, despite its transformative potential due to privacy, security, and data integrity features, faces challenges in widespread adoption. These challenges stem from vulnerabilities in consensus mechanisms, like Proof-of-Stake (PoS), and the lack of clear regulatory compliance frameworks. This research thesis addresses these challenges in two ways. Firstly, it focuses on enhancing PoS security by examining long-range attacks and leveraging Machine Learning techniques to classify nodes for effective mitigation. A novel dataset specifically designed for PoS node classification in permissionless blockchains is proposed to address this issue.

Secondly, the research tackles the evolving threat of host-based cryptojacking through CryptoJackingModel; a novel deep-learning model designed to outperform existing countermeasures by effectively detecting these attacks with minimal false positives and negatives. Finally, the research introduces a novel framework for assessing a blockchain application's regulatory readiness. A healthcare sector case study highlights the consequences of non compliance and underscores the need for a universally accepted regulatory framework. This framework offers guidance for navigating regulatory complexities and achieving regulatory readiness.

By addressing PoS security, cryptojacking threats, and regulatory compliance, this research significantly contributes to the advancement of secure and compliant blockchain applications. These findings provide valuable knowledge for stakeholders, regulators, and solution providers to effectively leverage the benefits of blockchain technology. Furthermore, the research paves the way for future investigations and fosters collaboration to establish robust regulatory frameworks that will facilitate the successful integration of blockchain technology across diverse sectors.
Date of AwardJun 2024
Original languageEnglish
Awarding Institution
  • University of Brighton
SupervisorMichalis Pavlidis (Supervisor) & Nikolaos Polatidis (Supervisor)

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