Prof. Dr. Tilmann Rabl

Vasiliki Kalavri

Affiliation: Boston University
Title: Secure and Expressive Time Series Analytics in Untrusted Clouds



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.

Short CV

Vasiliki (Vasia) Kalavri is an Assistant Professor of Computer Science at Boston University, where she co-leads the Complex Analytics and Scalable Processing (CASP) Systems lab. Vasia and her team enjoy doing research on multiple aspects of (distributed) data-centric systems. Recently, they have been working on self-managed systems for data stream processing, systems for scalable graph Machine Learning, and systems for secure collaborative analytics. Before joining BU, Vasia was a postdoctoral fellow at ETH Zurich and received a joint PhD from KTH (Sweden) and UCLouvain (Belgium). Vasia has received several awards for her research, including an IBM Innovation Award for her PhD Dissertation in 2017 and the SIGMOD Systems Award in 2023. Vasia’s research lab has received funding from the NSF, and industry awards from Google, Samsung, and RedHat.