Event-triggered state observers for sparse sensor noise/attacks

This paper describes two algorithms for state reconstruction from sensor measurements that are corrupted with sparse, but otherwise arbitrary, 'noise.' These results are motivated by the need to secure cyber-physical systems against a malicious adversary that can arbitrarily corrupt sensor measurements. The first algorithm reconstructs the state from a batch of sensor measurements while the second algorithm is able to incorporate new measurements as they become available, in the spirit of a Luenberger observer. A distinguishing point of these algorithms is the use of event-triggered techniques to improve the computational performance of the proposed algorithms

Contour: A Practical System for Binary Transparency

Transparency is crucial in security-critical applications that rely on authoritative information, as it provides a robust mechanism for holding these authorities accountable for their actions. A number of solutions have emerged in recent years that provide transparency in the setting of certificate issuance, and Bitcoin provides an example of how to enforce transparency in a financial setting. In this work we shift to a new setting, the distribution of software package binaries, and present a system for so-called "binary transparency." Our solution, Contour, uses proactive methods for providing transparency, privacy, and availability, even in the face of persistent man-in-the-middle attacks. We also demonstrate, via benchmarks and a test deployment for the Debian software repository, that Contour is the only system for binary transparency that satisfies the efficiency and coordination requirements that would make it possible to deploy today.Comment: International Workshop on Cryptocurrencies and Blockchain Technology (CBT), 201