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  • Textdokument
    Integrated Security Framework
    (INFORMATIK 2017, 2017) 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.
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    INFORMATIK 2017 WS#13
    (INFORMATIK 2017, 2017) 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.
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    Knowledge-Based Self-Organization of Traffic Control Systems
    (INFORMATIK 2017, 2017) 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.
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    Using Sensor Data of Widespread Smart Home Devices to Save Energy in Private Homes
    (INFORMATIK 2017, 2017) 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.
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    Pattern based decision tree analysis for risk detection in smart cities
    (INFORMATIK 2017, 2017) Scholz, Matthias; Piller:, Gunther; Eibl, Maximilian; Gaedke, Martin
    Increasing amounts of data on living environments and human interactions are becoming available. Their potential for valuable services improving the wellbeing of individuals is large and growing. This calls for an investigation of algorithms and system architectures that support possible use cases. In this paper we outline how pattern based decision tree analyses can be applied to the identification of risks caused by time-dependent effects from multiple influencing factors. For this purpose we apply the method to open data on car accidents and weather conditions. We also show how such systems can take advantage from up-to-date in-memory technology.
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    Smart Assistive User Interfaces in Private Living Environments
    (INFORMATIK 2017, 2017) Dörner, Ralf; Eibl, Maximilian; Gaedke, Martin
    The paper outlines a vision of how smart assistive user interfaces in private living environments could exceed the current state of the art. In particular, it is shown how a virtual assistant capable of evolution and capable of absorption is beneficial and a step towards an entity that is able to identify and make accessible through a user interface as many suitable services of the smart home environment as possible that fit the individual needs and interests of its users. Challenges such as the coherence challenge, the design challenge, the user acceptance challenge, and the security and privacy challenge are identified that are significant obstacles in realizing the vision. Based on this, approaches that provide a perspective to overcome these obstacles are presented. Here, the paper looks at advanced UI technology, robotics, user profiling and smart reasoning, software architectures, the internet of things, organic computing, and advanced security methodologies. Finally, the paper discusses a blueprint for a smart assistive user interface and the peculiarities in the application field of private living environments.
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    Smart Authoring for Location-based Augmented Reality Storytelling Applications
    (INFORMATIK 2017, 2017) Kampa, Antonia; Spierling, Ulrike; Eibl, Maximilian; Gaedke, Martin
    SPIRIT has been an applied research project that developed a location-based Augmented Reality prototype for outdoor museums. It uses the sensors of mobile consumer appliances to provide a variety of contexts for the delivery of adaptive and interactive stories. This paper addresses the technical authoring process to develop new non-linear story content for the app. We propose smart authoring tools to assist non-programmers. Based on requirements for authoring that we identified from issues in our first production, we describe the smart authoring tools MockAR, StoryPlaceAR, StoryStructAR and VideoTestAR. Preliminary evaluation observations support our hypothesis that these tools simplify the authoring process, in order to support museum curators and media designers during the creation of mobile experiences adapted to contextual situations.
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    Deep Convolutional Neural Networks for Pose Estimation in Image-Graphics Search
    (INFORMATIK 2017, 2017) Eberts, Markus; Ulges, Adrian; Eibl, Maximilian; Gaedke, Martin
    Deep Convolutional Neural Networks (CNNs) have recently been highly successful in various image understanding tasks, ranging from object category recognition over image classification to scene segmentation. We employ CNNs for pose estimation in a cross-modal retrieval system, which -given a photo of an object -allows users to retrieve the best match from a repository of 3D models. As our system is supposed to display retrieved 3D models from the same perspective as the query image (potentially with virtual objects blended over), the pose of the object relative to the camera needs to be estimated. To do so, we study two CNN models. The first is based on end-to-end learning, i.e. a regression neural network directly estimates the pose. The second uses transfer learning with a very deep CNN pre-trained on a large-scale image collection. In quantitative experiments on a set of 3D models and real-world photos of chairs, we compare both models and show that while the end-to-end learning approach performs well on the domain it was trained on (graphics) it suffers from the capability to generalize to a new domain (photos). The transfer learning approach on the other hand handles this domain drift much better, resulting in an average angle deviation from the ground truth angle of about 14 degrees on photos.
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    VCIT - Visually Corrected inertial Tracking
    (INFORMATIK 2017, 2017) Andrés López, Daniel; Diensberg, Benedikt; Schömer, Elmar; Schwanecke, Ulrich; Eibl, Maximilian; Gaedke, Martin
    Many smart systems depend on exact models of their environment. These are gained by tracking objects in their surroundings. When a highly precise system is only available for a small part of the environment, it can be enhanced with a second system to recover the unknown parts. This paper presents a method to recover loss of a precise (optical) tracking system by a less precise (inertial) tracking system. First the rotation from the inertial measurement unit (IMU) and the optical system are aligned. A second step integrates the IMU acceleration two times and removes both times the drift by known initial and end values (first integration: velocity, second integration: position) from optical tracking. The error is backpropagated continuously.
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    A Dense Statistical Model of Facial Soft Tissue Thickness
    (INFORMATIK 2017, 2017) Gietzen, Thomas; Brylka, Robert; Schwanecke, Ulrich; Schömer, Elmar; Eibl, Maximilian; Gaedke, Martin
    Ambient intelligence become more and more ubiquitous and help people achieving a more natural interaction with their electronically enhanced environment. One vital natural interface between humans and ambient intelligence are embodied conversational agents. Thereby, the acceptance of these virtual characters is all the greater, the more natural they look and behave. Since humans pay particular attention to the face, a natural-looking animation of the face is very important. In this paper we present a dense statistical model of facial soft tissue thickness that can be used to build accurate physics-based facial animations. The presented model not only can help to generate more natural facial animations of virtual characters but also can be used in other research domains such as forensic anthropology or medicine. Especially in the field of dentistry and orthodontics in particularly younger people and children are increasingly examined using X-ray technology. Thereby more and more volumetric images are generated, which further increase cost as well as the induced radiation dose. Here, for example, our statistical model can provide the basis for a new volumetric reconstruction process of a human’s facial bones in a cost-effective manner and with low radiation exposure.