http://dl.gi.de/handle/20.500.12116/21005 2026-07-21T13:01:43Z http://dl.gi.de/handle/20.500.12116/4123 Integrated Security Framework Gao, Yuan; Fischer, Robert; Seibt, Simon; Parekh, Mithil; Li, Jianghai Eibl, Maximilian; Gaedke, Martin The increasing cyber threats require quick action from security experts to protect their industrial automation control system (IACS). For fulfilling the requirement, we propose to divided the classic cyber security analysis scope into three separated, yet interconnected domains: Threat, System and Security. Thus different groups of security professionals can work independently, and are not required to have the knowledge about the full scope. In addition, we proposed an asset-centric system architecture model to enable the modeling and simulation of attacks according to publicly known threats and vulnerabilities. Analysis based on the generated attack/defense trees can assist to manage and continuously monitor the deployed security controls. The proposed approach with tool supports reduces the workload of security experts as well as the incidents response team (IRT) towards an adaptive defense manner. 2017-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/4122 INFORMATIK 2017 WS#13 de Meer, Jan; Waedt, Karl; Rennoch, Axel Eibl, Maximilian; Gaedke, Martin Der 2te internationale GI/ACM I4.0 Security Standardisation (ISS) Workshop auf der GI Jahrestagung 2017, fasst Sicherheits-gepaart mit Zuverlässigkeitsaspekten von Produktionsanlagen, z.B. in einer Smart Factory, die den Anforderungen der Multi-Teile-Norm IEC 62443[IEC14] für Industrielle Automatisierungs-und Kontrollsysteme (IACS) entspricht, genauer ins Auge. Industrieanlagen haben eine eigene inhärente Struktur, die in dem Referenz-Architekturmodell RAMI4.0 [ZVEI15], erstellt von einem Verbandskonsortium, geführt von ZVEI, skizziert ist. Diese Struktur fällt ins Gewicht, wenn ein Security-by-Design-Ansatz für verbundene, verteilte Industrieanlagen gewählt wird. Unter Sicherheit für IAC-Systemen werden hierbei im weitesten Sinne Systemeigenschaften und -fähigkeiten verstanden, die im sog. 'Pentagon of Trust' [JdM16] genannt werden, nämlich Vertrauen in vernetzte Produktionsanlagen und -geräten, Geheimhaltung von Fabrikationsdatensätzen, prüfbare Beachtung von Regulierungen und Gesetzen, Garantierung der Funktionalität von Produktionsanlagen und die einsichtige Anwendbarkeit von Anlagen und Geräten, was in ähnlicher Weise auch für vernetzte Geräte im sog. Internetz der Dinge (IoT -Internet of Things) gilt. Der 2te GI/ACM I4.0 WS strukturiert sich in die Handlungsgebiete: Architektur und Frameworks, Industrielle Erfahrung -Best Practice, Formalisierung und IACS Semantiken. 2017-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/4121 Knowledge-Based Self-Organization of Traffic Control Systems Jurisch, Matthias; Igler, Bodo Eibl, Maximilian; Gaedke, Martin Traffic control systems operating at the level of intersections can interact with each other. This interaction can be implicit (traffic flow) and explicit (exchange of sensor data). A central issue in this context is how to react to structural changes in a system of traffic control systems. This paper proposes to model all aspects which are relevant to the connection of these systems as ontologies. It further proposes to adapt to structural changes by taking inferences drawn from these ontologies into account. This work in progress is presented with the help of a concrete application example. A software prototype has been developed to demonstrate that this approach is technically feasible. 2017-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/4120 Using Sensor Data of Widespread Smart Home Devices to Save Energy in Private Homes Muth, Peter Eibl, Maximilian; Gaedke, Martin This paper proposes an approach for using sensor data of smart home devices to optimize energy consumption in private homes. For many years, radiator thermostats have been used to keep room temperatures at given desired levels. Smart home thermostats allow the temperature to be controlled by home automation software, advanced models are connected to sensors indicating open windows or sun shining into the room. In contrast to these advances, basic optimizations of the heating system like performing hydraulic balancing or minimizing flow temperature are rarely performed by the plumbers, because the optimization process is time consuming and requires data that are not available at installation time. In this paper, we describe how data delivered by smart home devices can be used to optimize the heating system. Using our approach, hydraulic balancing and minimizing flow temperature can be easily performed by the house owner without the help of a plumber, resulting in substantial energy savings. 2017-01-01T00:00:00Z