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Anonymous Communications against Global Adversaries via Secure Multi-Party Computation

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If you have a question about this talk, please contact Mani Bhesania.

Arguably, the engagement of citizens in internet communications increasingly demands the secure management of sensitive information. Privacy of personal data refers not only to context hiding, but also to the protection of metadata (e.g., time, location) associated with the communicating users. Unfortunately, current technologies that are deployed at a commercial level fail to provide an undoubtedly high level of privacy, as they either (i) offer protection restricted to the level of context hiding (end-to-end encryption – WhatsApp, Viber, Signal, Facebook Messenger) or (ii) are vulnerable against a “global adversary” that can monitor the entire network traffic (onion-routing – Tor).

In this talk, I will present MCMix [USENIX Security 2017], an anonymous messaging system that takes a novel design approach by applying Secure Multi-Party Computation (MPC) on fast oblivious sorting algorithms proposed by Hamada et al. [ICISC 2012]. By this approach, MCMix achieves provable security (“third-party” anonymity) against global adversaries, while in terms of performance it can scale at the order of 100K online users with reasonable latency (e.g.~1min for messages of SMS size). The MCMix system has been implemented over Cybernetica’s Sharemind MPC platform, and an application for Android clients is soon entering its testing period (Q2 2019). As a conclusion, I will describe how the core design idea of MCMix can be generalised to capture other interesting cases where communication privacy is desirable, such as order book matching in real-world trading scenarios.

This talk is part of the Computer Security Seminars series.

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