+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Freitag, 18. Juli 2025, 10:00 Uhr Ort: UMIC_025 (2165|025), Mies-van-der-Rohe-Str. 15, EG Referent: Andreas Klinger M.Sc. Lehr- und Forschungsgebiet IT-Sicherheit Thema: Variations of Secure Multi-Party Computation Abstract: Secure multi-party computation (SMPC) enables multiple parties to evaluate functions over their private inputs such that none of the parties can learn anything about the other parties’ private inputs and outputs but what can be deduced from their own input and output of the function evaluation. In classical SMPC it is assumed that the set of parties evaluating the function is fixed and a priori known. However, there are also online functionalities, in which parties arrive and leave over time, e. g., when providing possible dating recommendations, or finding other people for ride-sharing on the fly, where the personal preferences or start and destination should be kept private. Furthermore, in some applications participants may not only want to hide their private inputs and outputs, but may also want to hide the fact that they are participating in a given function evaluation in the first place, e. g., when checking the (private) DNA for a disease, then the participation in the check itself can already leak sensitive information. On the practical side of SMPC, the performance and applicability of SMPC protocols is typically evaluated with extensive benchmarking in varying settings, e. g., different number of parties, problem sizes, and network settings. However, evaluating the performance of SMPC protocols can be very time and resource consuming, as SMPC protocols typically introduce a considerable performance overhead compared to non-privacy-preserving computations. In this work we will extend the classical notions of SMPC to allow the secure evaluation of online functionalities in a distributed fashion. We present the notion of an online trusted third party that allows to prove the security of SMPC protocols implementing online functionalities. We also show in a general feasibility result that online functionalities can be implemented in a privacy-preserving fashion. In addition, we present two privacy-preserving online SMPC protocols for the online problem “fully online matching with deadlines”. In this problem an (a priori unknown) set of parties arrives with their inputs over time and can then be matched with other parties until they leave when their individual deadline is reached. We explore the performance of our protocols in an extensive evaluation. Furthermore, we present an anonymous system for SMPC that allows parties to anonymously evaluate an (offline) functionality in a fully distributed and secure fashion. The overall system provides robustness with penalty against a dishonest majority in the presence of a malicious adversary. Finally, we present an approach to estimating the runtime and global network traffic of SMPC protocols. We implemented this approach in the tool XENON, and show its estimation capabilities in an extensive evaluation. In addition, we present a second tool called NEON that simplifies the benchmarking of SMPC protocols, which might be of independent interest. Es laden ein: die Dozentinnen und Dozenten der Informatik