Development and Validation of Security Metrics and Predictive Models for Blockchain Ecosystems

Background:

Blockchain technology is a transformative innovation that has the potential to disrupt various sectors including finance, healthcare, and governance. However, with its growing adoption, security remains a critical concern. Recent high-profile security breaches have emphasized the need for robust security measures within blockchain and cryptocurrency ecosystems.

Scope of Work:

The PhD candidate will contribute to:-

Develop and validate security metrics applicable to blockchain protocols and smart contracts.- Utilize machine learning techniques to build predictive models aimed at early identification of security risks.- Analyze real-world blockchain data to test the developed metrics and models.- Prepare research outputs, including journal and conference papers, to disseminate findings.

Collaborative Opportunities:

The project offers the opportunity for collaboration with industry and academic partners (UCL) and external stakeholders. This includes work with blockchain development companies, cybersecurity firms, and academic collaborators for joint research and publications.

Required Prior Knowledge:

The ideal candidate should possess a strong background in computer science, with specialised skills in data science, machine learning. An understanding of blockchain is also highly desirable.

This research will provide an academically rigorous yet industry-relevant contribution to the evolving domain of blockchain security, ensuring both the theoretical and practical impact of the work.