Consensus encalpsulates the inherent problems of building fault tolerant distributed systems. In this context, the classic model of Byzantine faulty processes can be restated such that messages from a subset of processes can be arbitrarily corrupted (including addition and omission of messages).We consider the case of dynamic and transient faults, that may affect all processes and that are not permanent, and we model them via corrupted communication. For corrupted communication it is natural to distinguish between the safety of communication, which is concerned with the number of altered messages, and the liveness of communication, which restricts message loss.We present two consensus algorithms, together with sufficient conditions on the system to ensure correctness. Our first algorithm needs strong conditions on safety but requires weak conditions on liveness in order to terminate. Our second algorithm tolerates a lower degree of communication safety at the price of stronger liveness conditions.Our algorithms allow us to circumvent the resilience lower bounds from Santoro/Widmayer and Martin/Alvisi.

In the area of the Internet of Things, cloud-based camera surveillance systems are ubiquitously available for industrial and private environments. However, the sensitive nature of the surveillance use case imposes high requirements on privacy/confidentiality, authenticity, and availability of such systems. In this work, we investigate how currently available mass-market camera systems comply with these requirements. Considering two attacker models, we test the cameras for weaknesses and analyze for their implications. We reverse-engineered the security implementation and discovered several vulnerabilities in every tested system. These weaknesses impair the users' privacy and, as a consequence, may also damage the camera system manufacturer's reputation. We demonstrate how an attacker can exploit these vulnerabilities to blackmail users and companies by denialof-service attacks, injecting forged video streams, and by eavesdropping private video data -even without physical access to the device. Our analysis shows that current systems lack in practice the necessary care when implementing security for IoT devices.

Consensus is one of the key problems in fault tolerant distributed computing. A very popular model for solving consensus is the failure detector model defined by Chandra and Toueg. However, the failure detector model has limitations. The paper points out these limitations, and suggests instead a model based on communication predicates, called HO model. The advantage of the HO model over failure detectors is shown, and the implementation of the HO model is discussed in the context of a system that alternates between good periods and bad periods. Two definitions of a good period are considered. For both definitions, the HO model allows us to compute the duration of a good period for solving consensus. Specifically, the model allows us to quantify the difference between the required length of an initial good period and the length of a non initial good period.

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