Paper accepted at USENIX Security ’23

Our paper “TVA: A multi-party computation system for secure and expressive time series analytics“, authored by Muhammad Faisal, Jerry Zhang, John Liagouris, Vasiliki Kalavri, and Mayank Varia, was accepted for publication at USENIX Security ’23.

TVA is a multi-party computation system for secure analytics on secret-shared time series data that achieves high expressivity, by enabling complex analytics on inputs with unordered and irregular timestamps, and strong security guarantees in the semi-honest and malicious settings. TVA is the first system to support arbitrary composition of oblivious window operators, keyed aggregations, and multiple filter predicates, while keeping all data attributes private, including record timestamps and user-defined values in query predicates.

We look forward to presenting this work at USENIX Security in August!