SEPIA: Privacy-Preserving Aggregation of Multi-Domain Network Events and Statistics

Secure multiparty computation (MPC) allows joint privacy-preserving computations on data of multiple parties. Although MPC has been studied substantially, building solutions that are practical in terms of computation and communication cost is still a major challenge. In this paper, we investigate the practical usefulness of MPC for multi-domain network security and monitoring. We first optimize MPC comparison operations for processing high volume data in near real-time. We then design privacy-preserving protocols for event correlation and aggregation of network traffic statistics, such as addition of volume metrics, computation of feature entropy, and distinct item count. Optimizing performance of parallel invocations, we implement our protocols along with a complete set of basic operations in a library called SEPIA. We evaluate the running time and bandwidth requirements of our protocols in realistic settings on a local cluster as well as on PlanetLab and show that they work in near ...

• Type: Journal
• Year: 2010
• Where: USS
• Authors: Martin Burkhart, Mario Strasser, Dilip Many, Xenofontas A. Dimitropoulos
• Keywords: Computation, MPC Comparison Operations, Operating System, Secure Multiparty Computation, USS 2010