Enhancing Security Through Task Migration in Software-Defined Vehicles

<p>The growing trend of software-controlled operation, control, and development of modern vehicles has led to the emergence of the software-defined vehicle (SDV) design paradigm. SDVs contain increasing software components and, like other cyber-physical systems, are more susceptible to cyber-attacks. However, patching vulnerabilities in these systems may take time, exposing them to cyber threats. To limit the effect of an attack, one solution is to migrate critical tasks co-located on the same electronic control unit (ECU) with a compromised component to another ECU. However, existing migration solutions, often designed for fault tolerance, introduce overhead and ignore security parameters. This article introduces ShiftGuard, a security-aware, distributed task migration mechanism for SDVs. We explore various design decisions that may affect the performance of ShiftGuard. We implemented and demonstrated the efficacy of ShiftGuard on an automotive platform running the controller area network (CAN) protocol and found that the end-to-end latency of the task migration decision is less than 17 ms for a system with 15 tasks hosted in three ECUs. We also performed extensive design-space exploration using a custom-developed simulator. Our experiments with synthetic workloads show that any task migration request has a 76%–100% success rate. In addition, we demonstrate ShiftGuard’s scalability for large networks of up to 70 ECUs, making it highly suitable for automotive systems with SDV capabilities.</p>

Authors

Institutions

Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-09-18
DOI
https://doi.org/10.1109/jiot.2025.3611875
Citations
1
Primary Topic
Real-Time Systems Scheduling
Type
article
Field-Weighted Citation Impact
2.27

Funders

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article

Enhancing Security Through Task Migration in Software-Defined Vehicles

Daniel Lüdtke, Monowar Hasan, Zain A. H. Hammadeh, Mohammad Hamad et al.
1 citations
IEEE Internet of Things Journal
Real-Time Systems Scheduling
2.27
article

Enhancing Security Through Task Migration in Software-Defined Vehicles

Daniel Lüdtke, Monowar Hasan, Zain A. H. Hammadeh, Mohammad Hamad, Sebastian Steinhorst, Mert D. Pesé, Davide Alessi
article en
1 citations

Abstract

<p>The growing trend of software-controlled operation, control, and development of modern vehicles has led to the emergence of the software-defined vehicle (SDV) design paradigm. SDVs contain increasing software components and, like other cyber-physical systems, are more susceptible to cyber-attacks. However, patching vulnerabilities in these systems may take time, exposing them to cyber threats. To limit the effect of an attack, one solution is to migrate critical tasks co-located on the same electronic control unit (ECU) with a compromised component to another ECU. However, existing migration solutions, often designed for fault tolerance, introduce overhead and ignore security parameters. This article introduces ShiftGuard, a security-aware, distributed task migration mechanism for SDVs. We explore various design decisions that may affect the performance of ShiftGuard. We implemented and demonstrated the efficacy of ShiftGuard on an automotive platform running the controller area network (CAN) protocol and found that the end-to-end latency of the task migration decision is less than 17 ms for a system with 15 tasks hosted in three ECUs. We also performed extensive design-space exploration using a custom-developed simulator. Our experiments with synthetic workloads show that any task migration request has a 76%–100% success rate. In addition, we demonstrate ShiftGuard’s scalability for large networks of up to 70 ECUs, making it highly suitable for automotive systems with SDV capabilities.</p>

IEEE Internet of Things JournalVol. 12(24)
Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE), Technical University of Munich (DE), Washington State University (US), Clemson University (US)
National Science Foundation, European Commission
Openalex Percentile: Top 12%
Real-Time Systems Scheduling
2.27
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