Abstract

This talk covers two recent works in computing analytical functions over encrypted data. I will start with the traditional range search problem and show how to encrypt data, such that it can be efficiently searched and stored, but is provably secure against attacks by a snap-shot attackers. The problem entails a definition of securely encrypting a datastructure. Our approach can withstand all recent attacks on property-preservingly encrypted databases. In the second part of the talk I will talk about the problem of computing rank functions over the blockchain. This can be used to implement sealed-bid auctions over the blockchain. Our approach is secure against malicious adversaries and requires only 3 to 4 blocks to compute. We combine a number of techniques in an usual way to achieve this trade-off.

Bio

Florian is an associate professor in the David R. Cheriton School of Computer Science at the University of Waterloo (since 2017) and executive director of the Waterloo Cybersecurity and Privacy Institute (since 2018). Before he worked as chief research expert at SAP in Karlsruhe (2005 – 2016) and as a software architect at Arxan Technologies in San Francisco (2002 – 2004). He holds a Ph.D. in computer science from the Karlsruhe Institute of Technology (2010) and a master's degree from Purdue University (2001). He is interested in data security and privacy in data management, machine learning, and blockchains. He extends real-world systems with cryptographic security mechanisms to achieve (some) provable security guarantees.