Comparative Analysis of Leakage Tools on Scalable Case Studies
Abstract
Quantitative security techniques have been proven effective to measure the security of systems against various types of attackers. However, such techniques are often tested against small-scale academic examples. In this paper we use analyze two scalable, real life privacy case studies: the privacy of the energy consumption data of the users of a smart grid network and the secrecy of the voters' voting preferences with different types of voting protocols. We analyze both case studies with three state-of-the-art information leakage computation tools: LeakWatch, Moped-QLeak, and our tool QUAIL equipped with a new trace analysis algorithm. We highlight the relative advantages and drawbacks of the tools and compare their usability and effectiveness in analyzing the case studies.
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