Paper 2025/322

Partial and Fully Homomorphic Matching of IP Addresses Against Blacklists for Threat Analysis

Abstract

In many areas of cybersecurity, we require access to Personally Identifiable Information (PII), such as names, postal addresses and email addresses. Unfortunately, this can lead to data breaches, especially in relation to data compliance regulations such as GDPR. An IP address is a typical identifier which is used to map a network address to a person. Thus, in applications which are privacy-aware, we may aim to hide the IP address while aiming to determine if the address comes from a blacklist. One solution to this is to use homomorphic encryption to match an encrypted version of an IP address to a blacklisted network list. This matching allows us to encrypt the IP address and match it to an encrypted version of a blacklist. In this paper, we use the OpenFHE library \cite{OpenFHE} to convert network addresses into the BFV homomorphic encryption method. In order to assess the performance impact of BFV, it implements a matching method using the OpenFHE library and compares this against the partial homomorphic methods of Paillier, Damgard-Jurik, Okamoto-Uchiyama, Naccache-Stern and Benaloh. The main findings are that the BFV method compares favourably against the partial homomorphic methods in most cases.