Investigating Financial Risks in the Monetary System of Cryptocurrencies

While the rising of the Internet of Things is rapidly expanding the digital landscape of business technology, corporations become highly exposed to information risks and more concerned with cybersecurity issues related to their infrastructure and environment. The financial sector is one of the most targeted sectors by cybercrime due to the central role of digitization in the credit intermediation activities.

Cybersecurity is evolving into a global-wide economic issue rather than only a technology risk. As reported by the World Economic Forum, the fraud and financial crime is a trillion-dollar industry. Hence, financial cybersecurity events and their impacts need to be properly modelled, interpreted and handled.

This project aims at developing a robust modelling framework to assess and quantify cyber risk and to allocate resources to manage cybersecurity in the financial system. It develops a candidate with knowledge and skills in information technology, banking, accounting and finance, data science, etc. Especially, the doctoral research project integrates cutting-edge methodologies in computer science (e.g.

Artificial intelligence, deep learning), finance, system engineering and mathematics. It is interdisciplinary and aims to cover the following aspects that centre on cybersecurity issues faced by the financial industry: detecting security incidents in the financial system using deep learning algorithms;

using Hawkes processes to model the contagious feature of cyberattacks and fraud activities; defining and quantifying the financial system vulnerability and instability; building financial cyber-risk rating models.