Stream processing provides an appealing paradigm for building large-scale distributed applications. Such applications are often deployed over multiple administrative domains, some of which may not be trusted. Recent attacks in public clouds indicate that a major concern in untrusted domains is the enforcement of privacy. In this talk we will primarily focus on the problem of content-based routing (CBR), which is at the core of many event stream processing systems. By routing data based on subscriptions evaluated on the content of publications, CBR systems can expose critical information to unauthorized parties. Information leakage can be avoided by the means of privacy-preserving filtering, which is supported by several mechanisms for encrypted matching. Unfortunately, existing approaches have in common a high performance overhead and the difficulty to use classical optimization. We will present and discuss mechanisms that greatly reduces the cost of supporting privacy-preserving filtering based on encrypted matching operators.
Pascal Felber received his M.Sc. and Ph.D. degrees in Computer Science from the Swiss Federal Institute of Technology. From 1998 to 2002, he has worked at Oracle Corporation and Bell-Labs (Lucent Technologies) in the USA. From 2002 to 2004, he has been an Assistant Professor at Institut EURECOM in France. Since October 2004, he is a Professor of Computer Science at the University of Neuchâtel, Switzerland, working in the field of dependable and distributed systems. He has published over 100 research papers in various journals and conferences.
Paulo Jorge Pires Ferreira