Secure computation of fan-in and fan-out degree of nodes using additive homomorphic encryption
D.E. Floroiu (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Z Erkin – Mentor (TU Delft - Cyber Security)
Kubilay Atasu – Mentor (TU Delft - Data-Intensive Systems)
M. Khosla – Graduation committee member (TU Delft - Multimedia Computing)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
There is an increasing need for financial institutions to be able to detect illicit activities such as money laundering. While these institutions currently rely on graph-based analytics or machine learning algorithms for such detection, inter-bank collaboration is hindered by privacy concerns and regulations. In this paper, we introduce a new protocol for computing simple fundamental graph features (specifically fan-in and fan-out degrees) directly on encrypted transaction data using the advantages of additive homomorphic encryption schemes, especially the Paillier cryptosystem. Our algorithm allows a semi-trusted third party to perform computations without accessing plaintext data, enabling privacy-preserving collaboration between banks. Through the paper, we detail the protocol design, analyze its complexity, security and correctness, and demonstrate how it reduces the gap between utility and privacy. While the protocol currently supports only basic graph metrics and assumes a common normalized currency, it offers a scalable and practical foundation for future privacy-preserving financial crime analytics.