The Internet of Things (IoT) is a ubiquitous system connecting many different devices -the things -which can be accessed from the distance. The cyber-physical systems (CPS) monitor and control the things from the distance. As a result, the concepts of dependability and security get deeply intertwined. The increasing level of dynamicity, heterogeneity, and complexity adds to the system's vulnerability, and challenges its ability to react to faults. This paper summarizes state-of-the-art of existing work on anomaly detection, fault-tolerance and self-healing, and adds a number of other methods applicable to achieve resilience in an IoT. We particularly focus on non-intrusive methods ensuring data integrity in the network. Furthermore, this paper presents the main challenges in building a resilient IoT for CPS which is crucial in the era of smart CPS with enhanced connectivity (an excellent example of such a system is connected autonomous vehicles). It further summarizes our solutions, work-in-progress and future work to this topic to enable "Trustworthy IoT for CPS". Finally, this framework is illustrated on a selected use case: A smart sensor infrastructure in the transport domain.

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Abstract. This paper addresses the problem of safely navigating a mobile robot with limited sensing capability and limited information about stationary obstacles. We consider two sensing limitations: blind spots between sensors and limited sensing range. We identify a set of constraints on the sensors' readings whose satisfaction at time t guarantees collisionfreedom during the time interval [t, t+∆t]. Here, ∆t is a parameter whose value is bounded by a function of the maximum velocity of the robot and the range of the sensors. The constraints are obtained under assumptions about minimum internal angle and minimum edge length of polyhedral obstacles. We apply these constraints in the switching logic of the Simplex architecture to obtain a controller that ensures collision-freedom. Experiments we have conducted are consistent with these claims. To the best of our knowledge, our study is the first to provide runtime assurance that an autonomous mobile robot with limited sensing can navigate without collisions with only limited information about obstacles.

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