Matchmaking has become a prevalent part in contemporary applications, being used in dating apps, social media, online games, contact tracing and in various other use-cases. However, most implementations of matchmaking require the collection of sensitive/personal data for proper functionality. As such, with this work we aim to reduce the privacy leakage inherent in matchmaking applications. We propose H-Elo, a Fully Homomorphic Encryption (FHE)-based, private rating system, which allows for secure matchmaking through the use of traditional rating systems. In this work, we provide the construction of H-Elo, analyse the security of it against a capable adversary as well as benchmark our construction in a chess-based rating update scenario. Through our experiments we show that H-Elo can achieve similar accuracy to a plaintext implementation, while keeping rating values private and secure. Additionally, we compare our work to other private matchmaking solutions as well as cover some future directions in the field of private matchmaking. To the best of our knowledge we provide one of the first private and secure rating system-based matchmaking protocols.

翻译：匹配已成为当代应用中普遍存在的功能，广泛应用于约会软件、社交媒体、在线游戏、接触追踪及其他多种场景。然而，大多数匹配实现需收集敏感/个人数据才能正常运行。因此，本研究旨在减少匹配应用中固有的隐私泄露问题。我们提出H-Elo——一种基于全同态加密（FHE）的私有评分系统，通过利用传统评分系统实现安全匹配。本文构建了H-Elo方案，分析了其面对强敌手的安全性，并在基于国际象棋的评分更新场景中对其性能进行了基准测试。实验表明，H-Elo能在保持评分值私密安全的同时，达到与明文实现相近的精度。此外，我们将本研究与其他私密匹配方案进行了对比，并探讨了私密匹配领域的未来方向。据我们所知，这是首个基于私有且安全的评分系统的匹配协议之一。