Biblio

Anonymity is an essential asset for a variety of communication systems, like humans' communication, the internet of things, and sensor networks. Establishing and maintaining such communication systems requires the exchange of information about their participants (called subjects). However, protecting anonymity reduces the availability of subject information, as these can be leveraged to break anonymity. Additionally, established techniques for providing anonymity often reduce the efficiency of communication networks. In this paper, we model four mechanisms to share routing information and discuss them with respect to their influence on anonymity and efficiency. While there is no ``one fits all'' solution, there are suitable trade-offs to establish routing information complying with the technical capabilities of the subjects. Distributed solutions like decentralized lookup tables reduce routing information in messages at the cost of local memory consumption; other mechanisms like multi-layer encrypted path information come with higher communication overhead but reduce memory consumption for each subject.

With the rapidly increasing number of Internet of Things (IoT) devices and their extensive integration into peoples' daily lives, the security of those devices is of primary importance. Nonetheless, many IoT devices suffer from the absence, or the bad application, of security concepts, which leads to severe vulnerabilities in those devices. To achieve early detection of potential vulnerabilities, network scanner tools are frequently used. However, most of those tools are highly specialized; thus, multiple tools and a meaningful correlation of their results are required to obtain an adequate listing of identified network vulnerabilities. To simplify this process, we propose a modular framework for automated network reconnaissance and vulnerability indication in IP-based networks. It allows integrating a diverse set of tools as either, scanning tools or analysis tools. Moreover, the framework enables result aggregation of different modules and allows information sharing between modules facilitating the development of advanced analysis modules. Additionally, intermediate scanning and analysis data is stored, enabling a historical view of derived information and also allowing users to retrace decision-making processes. We show the framework's modular capabilities by implementing one scanner module and three analysis modules. The automated process is then evaluated using an exemplary scenario with common IP-based IoT components.

Graph pattern matching in network topologies is a building block of many distributed algorithms. Based on a limited local view of the topology, pattern-based algorithms substantiate the decision-making of each device on the occurrence of graph patterns in its surrounding topology. Existing pattern-based algorithms require that each device has a sufficiently large local view to match patterns without support of other devices. In practical environments, the local view is often restricted to one hop. Thus, algorithms matching non-trivial patterns are locked out from such environments today. This paper presents the first algorithm for distributed topology pattern matching, enabling pattern matching beyond the local view. Outgoing from initiating devices, our pattern matcher delegates the matching procedure to further devices in the network. Exploring major contextual parameters of our algorithm, we show that the optimal local view size depends on scenario-specific conditions. Our pattern matcher provides the flexibility for adaptations of the local view size at runtime. Making use of this flexibility, we optimize the execution of an established pattern-based algorithm and evaluate our pattern matcher in two topology control case studies for the Internet of Things. By scaling the view size of each device in a distributed way, our adaptive approach achieves significant communication cost savings in face of dynamic conditions.

Smart Grids (SGs) are Critical Infrastructures (CI), which are responsible for controlling and maintaining the distribution of electricity. To manage this task, modern SGs integrate an Information and Communication Infrastructure (ICT) beside the electrical power grid. Aside from the benefits derived from the increasing control and management capabilities offered by the ICT, unfortunately the introduction of this cyber layer provides an attractive attack surface for hackers. As a consequence, security becomes a fundamental prerequisite to be fulfilled. In this context, the adoption of Systems Engineering (SE) tools combined with Modeling and Simulation (M&S) techniques represent a promising solution to support the evaluation process of a SG during early design stages. In particular, the paper investigates on the identification, modeling and assessment of attacks in SG environments, by proposing a model for representing attack scenarios as a combination of attack types, attack schema and their temporal occurrence. Simulation techniques are exploited to enable the execution of such attack combinations in the SG domain. Specifically, a simulator, which allows to assess the SG behaviour to identify possible flaws and provide preventive actions before its realization, is developed on the basis of the proposed model and exemplified through a case study.