Enabling secure outsourced analytics with practical performance has been a long-standing research challenge in the databases and systems communities. In this talk, I will present our work towards realizing this vision with TVA (SECURITY’23), a new framework for secure time series analytics in untrusted clouds. TVA targets collaborative analytics, where data owners (hospitals, companies, research institutions, or individuals) are willing to allow certain computations on their collective private data, provided that data remain siloed from untrusted entities. To ensure no information leakage and provable security guarantees, our work relies on cryptographically secure Multi-Party Computation (MPC). I will introduce TVA’s protocols for secure window assignment and describe the time series operators that enable it to support both snapshot and recurring queries on private inputs with unordered and irregular timestamps.