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Institute
Die zunehmende Digitalisierung auch in Kraftwerken erfordert entsprechend auf diesen Bereich zugeschnittene IT-Sicherheitsverfahren und -technologien. Aktuell stellt die obligatorische Implementierung eines angemessenen Sicherheitsprozesses, wie eines Informationssicherheitsmanagementsystems (ISMS), Betreiber von Erzeugungsanlagen, Energienetzen und anderen kritischen Infrastrukturen vor eine große Herausforderung, denn es gilt, zahlreiche Anforderungen bei der Implementierung zu erfüllen, ohne dass konkrete Methoden zur Umsetzung verfügbar sind. Gleichzeitig ist derEinsatz von IT-Sicherheitstechnologien aus der Bürowelt aufgrund gänzlich anderer Eigenschaften und Anforderungen industrieller Netze kaum möglich. Zur Adressierung dieser Problematik wurden von der Brandenburgischen Technischen Universität Cottbus-Senftenberg (BTU) und der Lausitz Energie Kraftwerke AG (LEAG) innovative Verfahren zur (1) systematischen Bewertung sowie (2) Verbesserung der IT-Sicherheit in hochsensiblen Netzen konzipiert und prototypisch implementiert, die
ein diesem Beitrag mit den zugehörigen Forschungsprojekten vorgestellt werden. Um eine Beeinflussung empfindlicher Kraftwerksanlagen auszuschließen, wurde für alle Methoden ein nichtintrusiver Entwicklungsansatz verfolgt, der sich durch eine passive und vom jeweiligen industriellen Prozess vollständig entkoppelte Analyse auszeichnet und sich daher für einen breiten Einsatz in Netzen mit hohen Verfügbarkeitsanforderungen eignet.
TSN Scheduler Benchmarking
(2023)
Time-Sensitive Networking (TSN) disrupts realtime communication technology by making IEEE Ethernet realtime-capable. For time-triggered, hard realtime traffic, TSN provides standardized mechanisms to reserve communication paths as well as individual transmission time slots for data frames. By leveraging these means in a precomputed network schedule, TSN allows for bounded end-to-end delays and minimal jitter. Not being part of the IEEE standard, corresponding scheduling algorithms are an active field of research. Unfortunately, due to differing model assumptions, evaluation setups, and key metrics, a fair comparison of schedulers is impossible so far. In this paper, we present a systematic and reproducible approach to benchmark TSN schedulers. First, we provide a scheduler taxonomy that enables to cluster schedulers by their characteristics. Second, we analyze interactions of input parameters and scheduler results to derive a benchmarking parcour for quantitative comparisons. Finally, we use the approach to benchmark existing schedulers and show subtle interaction effects. This way, our approach enables—for the first time-comparability between schedulers, fueled by the public availability of our benchmarking scenarios.
Due to demographic changes in developed industrial countries and a better medical care system, the number of elderly people who still live in their home environment is rapidly growing because there they feel more comfortable and independent as in a clinical environment or in a residential care home. The elderly often live alone and receive only irregular visits. Due to impaired physical skills the probability of falls significantly increases. The detection of falls is a crucial aspect in the care of elderly. Falls are often detected very late with severe consequential damages. There are existing approaches for automatic fall detection. They usually deploy special external devices. Elderly people often do not accept these devices because they expose their frailty. In this paper, we present a location-independent fall detection method implemented as a smartphone application for an inconspicuous use in nearly every situation of the daily life. The difficulty of our approach is in the low resolution range of integrated acceleration sensors and the limited energy supply of the smartphone. As solution, we apply a modular threshold-based algorithm which uses the acceleration sensor with moderate energy consumption. Its fall detection rate is in the average of current relevant research.
Industrial Control Systems (ICS) are critical systems to our society. Yet they are less studied given their closed nature and often the unavailability of data. While few studies focus on wide-area SCADA systems, e.g., power or gas distribution networks, mission critical networks that control power generation are not yet studied. To address this gap, we perform the first measurement study of Distributed Control System (DCS) by analyzing traces from all network levels from several operational power plants. We show that DCS networks feature a rather rich application mix compared to wide-area SCADA networks and that applications and sites can be fingerprinted with statistical means. While traces from operational power plants are hard to obtain, we analyze to which extent easier to access training facilities can be used as vantage points. Our study aims to shed light on traffic properties of critical industries that were not yet analyzed given the lack of data.
Current developments in digitization and industry 4.0 bear new challenges for automation systems. In order to enable interoperability and vertical integration of corporate management systems, these networks have evolved from formerly proprietary solutions to the application of Ethernet-based communication and internet standards. This development is accompanied by an increase in the number of threats. Although the most critical IT protection objective for automation systems is availability, usually no security mechanisms have been integrated into automation protocols. Also Ethernet offers no protection by design for these protocols. One of the most popular real-time protocols for industrial applications is Profinet IO. In this paper, we describe a Denial-of-Service attack on Profinet IO that exploits a vulnerability in the Discovery and Basic Configuration Protocol (DCP) which interrupts the Application Relationship between an IO Controller and an IO Device, and thus prevents the system from being repaired by the operator. The attack combines port stealing with the sending of forged DCP packets and causes a system downtime, which in affected production networks probably lead to a serious financial damage and, in case of critical infrastructures, even represents a high risk for the supply of society. We demonstrate the practical feasibility of the attack using realistic hardware and scenarios and discuss its significance for also other setups.