PhD Proposal 2023: Taxonomy of Frauds on Crypto-Assets
The thesis will be supervised under:
Abdessamad Imine (firstname.lastname@example.org)
Yamina Tadjeddine (email@example.com)
Deadline for application: August 15, 2023
Start date: October 1, 2023
We are looking for candidates with a Master’s degree combining computer science and economics and with good knowledge in the field of finance as well as crypto-assets. We may also consider candidates who have a master’s degree in financial economics or a master’s degree in computer science but who show real skills in the other discipline. In addition to a strong theoretical background in data analysis, we expect the candidate to have good Machine Learning and programming skills, with the ability to develop prototypes in Python. Candidates should have a passion for collaborating on interdisciplinary research and the academic skills to be part of a high-impact research team.
- Detailed CV (including a URL to download the pdf of the M.Sc. thesis – if applicable).
- Cover letter explaining why you are interested in this position, how your research interests relate to the topics mentioned in the project description above, and the relevant academic skills you have acquired (max: 2 pages).
- Copy of M.sc diploma and transcript of records.
- Name and contact details (including email address) of one or two academic referees who can recommend and provide details about your profile.
Description of PhD:
Keywords: crypto-asset; fraud; security; machine learning; regulation.
Based on peer-to-peer networks, crypto-assets are currently very popular in the world and are at the heart of several financial transactions/services such as participation in the financing of companies and associations, foreign currency loans, crypto-asset exchanges, and international money transfers. Against any state (or government) control, the community formed around crypto-asset users claims complete independence and trusts technology to protect the freedom and anonymity of its members. In this context, any form of public regulation is rejected, and self-regulation by individuals, or more precisely by IT infrastructures, is systematically favored.
Due to their decentralized nature and cypherpunk culture, financial services are supposed to be monitored by all members of the network and by the algorithms. Unfortunately, the recent history of crypto-assets highlights the limits of this control. Since 2009, the fragile security of DeFi transactions has been exposed by numerous events. Exchange hacks (Mt Gox in 2014, Coincheck in 2017, Poly Network in 2021, Wormhole in 2022) have resulted in the theft of wallets and loss of wealth for the parties involved. Many Ponzi schemes have also taken place, exploiting the gullibility of investors lured by the promise of quick riches. The year 2022 was particularly eventful with resounding bankruptcies of the stablecoin LUNA/TERRA in May and of the broker FTX in November. Additionally, crypto-assets are used by hackers to demand ransom payments in case of data theft.
This PhD thesis aims to review the current state of knowledge about current and potential types of fraud plaguing the Decentralized Finance (DeFi) space, and to provide comprehensive definitions of identified frauds in order to create IT and regulatory systems that prevent or report such frauds. The novelty of our approach lies in the fact of basing this research on an analysis based on two areas: economics and computer science. Indeed, the PhD candidate is expected to contribute to the design, analysis and development of original solutions for self-controlled security in DeFi. By combining algorithmic and machine learning approaches, the objective is to mitigate fraud impacts with high probability.