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Documents authored by Steinhorst, Sebastian

Document
DOI: 10.4230/LIPIcs.ECRTS.2025.6
Sensor Fusion Desynchronization Attacks

Authors: Andreas Finkenzeller, Andrew Roberts, Mauro Bellone, Olaf Maennel, Mohammad Hamad, and Sebastian Steinhorst

Published in: LIPIcs, Volume 335, 37th Euromicro Conference on Real-Time Systems (ECRTS 2025)

Abstract
Environmental perception and 3D object detection are key factors for advancing autonomous driving and require robust security measures to ensure optimal performance and safety. However, established methods often focus only on protecting the involved data and overlook synchronization and timing aspects, which are equally crucial for ensuring profound system security. For instance, multi-modal sensor fusion techniques for object detection can be affected by input desynchronization resulting from random communication delays or malicious cyber attacks, as these techniques combine various sensor inputs to extract shared features present in their data streams simultaneously. Current research acknowledges the importance of temporal alignment in this context. However, the presented studies typically assume genuine system behavior and neglect the potential threat of malicious attacks, as the suggested solutions lack strategies to prevent intentional data misalignment. Additionally, they do not adequately address how sensor input desynchronization affects fusion performance in depth. This paper investigates how desynchronization attacks impact sensor fusion algorithms for 3D object detection. We evaluate how varying sensor delays affect the detection performance and link our findings to the internal architecture of the sensor fusion algorithms and the influence of specific traffic scenarios and their dynamics. We compiled four datasets covering typical traffic scenarios for our empirical evaluation and tested them on four representative fusion algorithms. Our results show that all evaluated algorithms are vulnerable to input desynchronization, as the performance declines with increasing sensor delays, highlighting the existing lack of resilience to desynchronization attacks. Furthermore, we observe that the Light Detection and Ranging (LiDAR) sensor is significantly more susceptible to delays than the camera. Finally, our experiments indicate that the chosen fusion architecture correlates with the system’s resilience against desynchronization, as our results demonstrate that the early fusion approach provides greater robustness than others.
Cite as

Andreas Finkenzeller, Andrew Roberts, Mauro Bellone, Olaf Maennel, Mohammad Hamad, and Sebastian Steinhorst. Sensor Fusion Desynchronization Attacks. In 37th Euromicro Conference on Real-Time Systems (ECRTS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 335, pp. 6:1-6:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{finkenzeller_et_al:LIPIcs.ECRTS.2025.6,
  author =	{Finkenzeller, Andreas and Roberts, Andrew and Bellone, Mauro and Maennel, Olaf and Hamad, Mohammad and Steinhorst, Sebastian},
  title =	{{Sensor Fusion Desynchronization Attacks}},
  booktitle =	{37th Euromicro Conference on Real-Time Systems (ECRTS 2025)},
  pages =	{6:1--6:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-377-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{335},
  editor =	{Mancuso, Renato},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2025.6},
  URN =		{urn:nbn:de:0030-drops-235849},
  doi =		{10.4230/LIPIcs.ECRTS.2025.6},
  annote =	{Keywords: Security, Time Synchronization, Sensor Fusion, Autonomous Driving, Delay Attack}
}
Document
Artifact
DOI: 10.4230/DARTS.11.1.1
Sensor Fusion Desynchronization Attacks (Artifact)

Authors: Andreas Finkenzeller, Andrew Roberts, Mauro Bellone, Olaf Maennel, Mohammad Hamad, and Sebastian Steinhorst

Published in: DARTS, Volume 11, Issue 1, Special Issue of the 37th Euromicro Conference on Real-Time Systems (ECRTS 2025)

Abstract
Environmental perception and 3D object detection are key factors for advancing autonomous driving and require robust security measures to ensure optimal performance and safety. However, established methods often focus only on protecting the involved data and overlook synchronization and timing aspects, which are equally crucial for ensuring profound system security. For instance, multi-modal sensor fusion techniques for object detection can be affected by input desynchronization resulting from random communication delays or malicious cyber attacks, as these techniques combine various sensor inputs to extract shared features present in their data streams simultaneously. Current research acknowledges the importance of temporal alignment in this context. However, the presented studies typically assume genuine system behavior and neglect the potential threat of malicious attacks, as the suggested solutions lack strategies to prevent intentional data misalignment. Additionally, they do not adequately address how sensor input desynchronization affects fusion performance in depth. This paper investigates how desynchronization attacks impact sensor fusion algorithms for 3D object detection. We evaluate how varying sensor delays affect the detection performance and link our findings to the internal architecture of the sensor fusion algorithms and the influence of specific traffic scenarios and their dynamics. We compiled four datasets covering typical traffic scenarios for our empirical evaluation and tested them on four representative fusion algorithms. Our results show that all evaluated algorithms are vulnerable to input desynchronization, as the performance declines with increasing sensor delays, highlighting the existing lack of resilience to desynchronization attacks. Furthermore, we observe that the Light Detection and Ranging (LiDAR) sensor is significantly more susceptible to delays than the camera. Finally, our experiments indicate that the chosen fusion architecture correlates with the system’s resilience against desynchronization, as our results demonstrate that the early fusion approach provides greater robustness than others.
Cite as

Andreas Finkenzeller, Andrew Roberts, Mauro Bellone, Olaf Maennel, Mohammad Hamad, and Sebastian Steinhorst. Sensor Fusion Desynchronization Attacks (Artifact). In Special Issue of the 37th Euromicro Conference on Real-Time Systems (ECRTS 2025). Dagstuhl Artifacts Series (DARTS), Volume 11, Issue 1, pp. 1:1-1:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@Article{finkenzeller_et_al:DARTS.11.1.1,
  author =	{Finkenzeller, Andreas and Roberts, Andrew and Bellone, Mauro and Maennel, Olaf and Hamad, Mohammad and Steinhorst, Sebastian},
  title =	{{Sensor Fusion Desynchronization Attacks (Artifact)}},
  pages =	{1:1--1:3},
  journal =	{Dagstuhl Artifacts Series},
  ISSN =	{2509-8195},
  year =	{2025},
  volume =	{11},
  number =	{1},
  editor =	{Finkenzeller, Andreas and Roberts, Andrew and Bellone, Mauro and Maennel, Olaf and Hamad, Mohammad and Steinhorst, Sebastian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DARTS.11.1.1},
  URN =		{urn:nbn:de:0030-drops-236029},
  doi =		{10.4230/DARTS.11.1.1},
  annote =	{Keywords: Security, Time Synchronization, Sensor Fusion, Autonomous Driving, Delay Attack}
}
Document
Complete Volume
DOI: 10.4230/OASIcs.ASD.2020
OASIcs, Volume 79, ASD 2020, Complete Volume

Authors: Sebastian Steinhorst and Jyotirmoy V. Deshmukh

Published in: OASIcs, Volume 79, 2nd International Workshop on Autonomous Systems Design (ASD 2020)

Abstract
OASIcs, Volume 79, ASD 2020, Complete Volume
Cite as

2nd International Workshop on Autonomous Systems Design (ASD 2020). Open Access Series in Informatics (OASIcs), Volume 79, pp. 1-44, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@Proceedings{steinhorst_et_al:OASIcs.ASD.2020,
  title =	{{OASIcs, Volume 79, ASD 2020, Complete Volume}},
  booktitle =	{2nd International Workshop on Autonomous Systems Design (ASD 2020)},
  pages =	{1--44},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-141-2},
  ISSN =	{2190-6807},
  year =	{2020},
  volume =	{79},
  editor =	{Steinhorst, Sebastian and Deshmukh, Jyotirmoy V.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ASD.2020},
  URN =		{urn:nbn:de:0030-drops-125932},
  doi =		{10.4230/OASIcs.ASD.2020},
  annote =	{Keywords: OASIcs, Volume 79, ASD 2020, Complete Volume}
}
Document
Front Matter
DOI: 10.4230/OASIcs.ASD.2020.0
Front Matter, Table of Contents, Preface, Conference Organization

Authors: Sebastian Steinhorst and Jyotirmoy V. Deshmukh

Published in: OASIcs, Volume 79, 2nd International Workshop on Autonomous Systems Design (ASD 2020)

Abstract
Front Matter, Table of Contents, Preface, Conference Organization
Cite as

2nd International Workshop on Autonomous Systems Design (ASD 2020). Open Access Series in Informatics (OASIcs), Volume 79, pp. 0:i-0:x, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{steinhorst_et_al:OASIcs.ASD.2020.0,
  author =	{Steinhorst, Sebastian and Deshmukh, Jyotirmoy V.},
  title =	{{Front Matter, Table of Contents, Preface, Conference Organization}},
  booktitle =	{2nd International Workshop on Autonomous Systems Design (ASD 2020)},
  pages =	{0:i--0:x},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-141-2},
  ISSN =	{2190-6807},
  year =	{2020},
  volume =	{79},
  editor =	{Steinhorst, Sebastian and Deshmukh, Jyotirmoy V.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ASD.2020.0},
  URN =		{urn:nbn:de:0030-drops-125948},
  doi =		{10.4230/OASIcs.ASD.2020.0},
  annote =	{Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
DOI: 10.4230/OASIcs.ASD.2020.3
Adaptable Demonstrator Platform for the Simulation of Distributed Agent-Based Automotive Systems

Authors: Philipp Weiss, Sebastian Nagel, Andreas Weichslgartner, and Sebastian Steinhorst

Published in: OASIcs, Volume 79, 2nd International Workshop on Autonomous Systems Design (ASD 2020)

Abstract
Future autonomous vehicles will no longer have a driver as a fallback solution in case of critical failure scenarios. However, it is costly to add hardware redundancy to achieve a fail-operational behaviour. Here, graceful degradation can be used by repurposing the allocated resources of non-critical applications for safety-critical applications. The degradation problem can be solved as a part of an application mapping problem. As future automotive software will be highly customizable to meet customers' demands, the mapping problem has to be solved for each individual configuration and the architecture has to be adaptable to frequent software changes. Thus, the mapping problem has to be solved at run-time as part of the software platform. In this paper we present an adaptable demonstrator platform consisting of a distributed simulation environment to evaluate such approaches. The platform can be easily configured to evaluate different hardware architectures. We discuss the advantages and limitations of this platform and present an exemplary demonstrator configuration running an agent-based graceful degradation approach.
Cite as

Philipp Weiss, Sebastian Nagel, Andreas Weichslgartner, and Sebastian Steinhorst. Adaptable Demonstrator Platform for the Simulation of Distributed Agent-Based Automotive Systems. In 2nd International Workshop on Autonomous Systems Design (ASD 2020). Open Access Series in Informatics (OASIcs), Volume 79, pp. 3:1-3:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{weiss_et_al:OASIcs.ASD.2020.3,
  author =	{Weiss, Philipp and Nagel, Sebastian and Weichslgartner, Andreas and Steinhorst, Sebastian},
  title =	{{Adaptable Demonstrator Platform for the Simulation of Distributed Agent-Based Automotive Systems}},
  booktitle =	{2nd International Workshop on Autonomous Systems Design (ASD 2020)},
  pages =	{3:1--3:6},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-141-2},
  ISSN =	{2190-6807},
  year =	{2020},
  volume =	{79},
  editor =	{Steinhorst, Sebastian and Deshmukh, Jyotirmoy V.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ASD.2020.3},
  URN =		{urn:nbn:de:0030-drops-125974},
  doi =		{10.4230/OASIcs.ASD.2020.3},
  annote =	{Keywords: fail-operational, graceful degradation, agent-based mapping}
}
Document
DOI: 10.4230/DagRep.9.12.28
Future Automotive HW/SW Platform Design (Dagstuhl Seminar 19502)

Authors: Dirk Ziegenbein, Selma Saidi, Xiaobo Sharon Hu, and Sebastian Steinhorst

Published in: Dagstuhl Reports, Volume 9, Issue 12 (2020)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 19502 "Future Automotive HW/SW Platform Design". The goal of this seminar was to gather researchers and practitioners from academia and industry to discuss key industrial challenges, existing solutions and research directions in the design of future automotive HW/SW platforms, particularly focusing on predictability of systems regarding extra-functional properties, safe integration of hardware and software components and programmability and optimization of emerging heterogeneous platforms.
Cite as

Dirk Ziegenbein, Selma Saidi, Xiaobo Sharon Hu, and Sebastian Steinhorst. Future Automotive HW/SW Platform Design (Dagstuhl Seminar 19502). In Dagstuhl Reports, Volume 9, Issue 12, pp. 28-66, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@Article{ziegenbein_et_al:DagRep.9.12.28,
  author =	{Ziegenbein, Dirk and Saidi, Selma and Hu, Xiaobo Sharon and Steinhorst, Sebastian},
  title =	{{Future Automotive HW/SW Platform Design (Dagstuhl Seminar 19502)}},
  pages =	{28--66},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2020},
  volume =	{9},
  number =	{12},
  editor =	{Ziegenbein, Dirk and Saidi, Selma and Hu, Xiaobo Sharon and Steinhorst, Sebastian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.9.12.28},
  URN =		{urn:nbn:de:0030-drops-120101},
  doi =		{10.4230/DagRep.9.12.28},
  annote =	{Keywords: automotive, hw/sw platforms, real-time systems, systems design automation}
}
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