PhD Privacy Protected Federated Learning Algorithms for Credit Card Fraud Detection
PhD @Loughborough University posted 1 week agoJob Description
Project details
Amid the pandemic, we’ve seen how much digital connections for financial activities matter to daily life. While cyberattacks have tripled over the last decade, financial services remain the most targeted industry. According to the International Monetary Fund (IMF) report, cybersecurity is the new threat to financial stability. Credit card (CC) is considered an excellent target of fraud since a significant amount of money can be obtained quickly with low risk. However, CC transactions in each bank are extremely unbalanced – a few samples are fraudulent while a majority are legitimate. And the existing methods can only collect the CC data in each bank – due to various reasons, such as the GDPR in the EU and EEA, which leads to ‘data silos’; thus, the existing fraud detection system is prone to inefficient and has low accuracy. Recently, federated learning (FL) techniques have attracted researchers’ attention. Rare existing literature can handle the highly skewed data. Therefore, we plan to introduce robust statistical modelling into the FL and apply the proposed technique to the European CC transaction dataset. We also plan to apply the proposed model to an online stream dataset, which is capable of handling real-life situations.
94% of Loughborough’s research impact is rated world-leading or internationally excellent. REF 2021
Supervisors
Primary supervisor: Dr Peng Liu
Entry requirements
Our entry requirements are listed using standard UK undergraduate degree classifications i.e. first-class honours, upper second-class honours and lower second-class honours. To learn the equivalent for your country, please choose it from the drop-down below.
Entry requirements for United Kingdom
Applicants should have, or are expected to achieve, at least a 2:1 Honours degree (or equivalent) in Mathematics or in a related subject.
English language requirements
Applicants must meet the minimum English language requirements. Further details are available on the International website.
Applicants must meet the minimum English language requirements. Further details are available on the International website.
Fees and funding
Tuition fees for 2025-26 entry
UK fee
£5,006 Full-time degree per annum
International fee
£22,360 Full-time degree per annum
Fees for the 2025-26 academic year apply to projects starting in October 2025, January 2026, April 2026 and July 2026.
Tuition fees cover the cost of your teaching, assessment and operating University facilities such as the library, IT equipment and other support services. University fees and charges can be paid in advance and there are several methods of payment, including online payments and payment by instalment. Fees are reviewed annually and are likely to increase to take into account inflationary pressures.
How to apply
All applications should be made online. Under programme name, select Mathematical Scinences. Please quote the advertised reference number: MA/PL-SF2/2025 in your application.
To avoid delays in processing your application, please ensure that you submit a CV and the minimum supporting documents.
The following selection criteria will be used by academic schools to help them make a decision on your application. Please note that this criteria is used for both funded and self-funded projects.
Please note, applications for this project are considered on an ongoing basis once submitted and the project may be withdrawn prior to the application deadline, if a suitable candidate is chosen for the project.
