Juri Dispan

Subjective Logic (SL) is a mathematical framework for reasoning under uncertainty. It is useful for expressing opinions on how reliable information is (so-called Trust Opinions) and performing computations on these opinions. At our institute, we research applications of SL in the automotive domain, e.g. to express trust in data received from a sensor or from other vehicles. Current implementations of SL internally use floating-point arithmetic (IEEE 754) for performing calculations. However, IEEE 754 floating-point numbers are prone to introducing rounding errors. In safety-critical domains, failing to account for such errors might lead to catastrophic consequences. In this thesis/project, you will investigate the potential impact of floating-point errors in SL calculations and develop strategies to minimise it. You can choose your approach freely: whether you work theoretically (e.g. through a detailed study of literature) or practically (e.g. through implementing a test environment and explaining the observed effects) is up to you.

We introduce a combination of Shamir's secret sharing and dining-cryptographers networks, which provides (n-|attackers|))-anonymity for up to k-1 attackers and has manageable performance impact on dissemination. A k-anonymous broadcast can be implemented using a small group of dining cryptographers to first share the message, followed by a flooding phase started by group members. Members have little incentive to forward the message in a timely manner, as forwarding incurs costs, or they may even profit from keeping the message. In worst case, this leaves the true originator as the only sender, rendering the dining-cryptographers phase useless and compromising their privacy. We present a novel approach using a modified dining-cryptographers protocol to distributed shares of an (n, k)-Shamir's secret sharing scheme. All group members broadcast their received share through the network, allowing any recipient of k shares to reconstruct the message, enforcing anonymity. If less than k group members broadcast their shares, the message cannot be decoded thus preventing privacy breaches for the originator. We demonstrate the privacy and performance results in a security analysis and performance evaluation based on a proof-of-concept prototype. Throughput rates between 10 and 100 kB/s are enough for many real applications with high privacy requirements, e.g., financial blockchain system.

A k-anonymous broadcast can be implemented using a small group of dining cryptographers to first share the message, followed by a flooding phase started by group members. Members have little incentive to forward the message in a timely manner, as forwarding incurs costs, or they may even profit from keeping the message. In worst case, this leaves the true originator as the only sender, rendering the dining-cryptographers phase useless and compromising their privacy. We present a novel approach using a modified dining-cryptographers protocol to distributed shares of an (n,k)-Shamir's secret sharing scheme. Finally, all group members broadcast their received share through the network, allowing any recipient of k shares to reconstruct the message, enforcing anonymity. If less than k group members broadcast their shares, the message cannot be decoded thus preventing privacy breaches for the originator. Our system provides (n-|attackers|)-anonymity for up to k-1 attackers and has little performance impact on dissemination. We show these results in a security analysis and performance evaluation based on a proof-of-concept prototype. Throughput rates between 10 and 100 kB/s are enough for many real applications with high privacy requirements, e.g., financial blockchain system.