Issue
Leibniz Transactions on Embedded Systems, Volume 7, Issue 1
LITES, Volume 7, Issue 1
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LITES, Volume 7
Journal: Leibniz Transactions on Embedded Systems (LITES)
Publication Details
- published at: 2021-08-12
- Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
- DBLP: db/journals/lites/lites7
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Document
Complete Issue
LITES, Volume 7, Issue 1
Abstract
LITES, Volume 7, Issue 1
Cite as
LITES, Volume 7, Issue 1: Special Issue on Embedded System Security, pp. 1-64, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
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@Article{LITES-v007-i001,
title = {{LITES, Volume 7, Issue 1}},
journal = {Leibniz Transactions on Embedded Systems},
pages = {1--64},
ISSN = {2199-2002},
year = {2021},
volume = {7},
number = {1},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/LITES-v007-i001},
doi = {10.4230/LITES-v007-i001},
annote = {Keywords: LITES, Volume 7, Issue 1}
}
Document
Foreword
Foreword
Abstract
Embedded systems are now an integral part of our lives. We have smart phones, smart meters, smart appliances, smart cars, smart grids, and smart houses--most relying on embedded systems with outdated security mechanisms, if they have any at all. A renewed emphasis on embedded systems security research is critical to our economies and our daily lives. This special issue on Embedded System Security attempts to contribute to this work by drawing attention to a number of key topics including Intrusion Detection and Tolerance, Confidence and Threat Modelling, Enhancing Dependability in Embedded Systems, and reducing Vulnerabilities in System Architectures for Embedded Systems.
Two papers are included in this initial instalment of the Special Issue. In the first paper ``"Randomization as Mitigation of Directed Timing Inference Based Attacks on Time-Triggered Real-Time Systems with Task Replication" by Kristin Krüger, Nils Vreman, Richard Pates, Martina Maggio, Marcus Völp and Gerhard Fohler, the vulnerabilities of time-triggered systems are investigated. They note that the assumption that faults are independent, which is often made for accidental faults, is not valid for malicious attacks. They go on to introduce two runtime mitigation strategies to withstand directed timing inference. Both involve the introduction of a level of randomization within the usual deterministic behaviour of time-triggered systems.
In the second paper ``"We know what you're doing! Application detection using thermal data", Philipp Miedl, Rehan Ahmed and Lothar Thiele consider how sensitive runtime information can be extracted from a system by just using temperature sensor readings from a mobile device. They employ a Convolutional-Neural-Network to identify the sequence of executed applications over time. They test their hypothesis via collected data from two state-of-the-art smartphones and real user usage patterns. The accuracy of their finding demonstrated that this is a clear vulnerability in mobile devices, including the potential to compromise sensitive user data.
Cite as
LITES, Volume 7, Issue 1: Special Issue on Embedded System Security, p. 0:i, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
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@Article{burns_et_al:LITES.7.1.0,
author = {Burns, Alan and Goddard, Steve},
title = {{Foreword}},
journal = {Leibniz Transactions on Embedded Systems},
pages = {00:1--00:1},
ISSN = {2199-2002},
year = {2021},
volume = {7},
number = {1},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/LITES.7.1.0},
doi = {10.4230/LITES.7.1.0},
annote = {Keywords: Foreword, Embedded System Security}
}
Document
Randomization as Mitigation of Directed Timing Inference Based Attacks on Time-Triggered Real-Time Systems with Task Replication
Abstract
Time-triggered real-time systems achieve deterministic behavior using schedules that are constructed offline, based on scheduling constraints. Their deterministic behavior makes time-triggered systems suitable for usage in safety-critical environments, like avionics. However, this determinism also allows attackers to fine-tune attacks that can be carried out after studying the behavior of the system through side channels, targeting safety-critical victim tasks. Replication -- i.e., the execution of task variants across different cores -- is inherently able to tolerate both accidental and malicious faults (i.e. attacks) as long as these faults are independent of one another. Yet, targeted attacks on the timing behavior of tasks which utilize information gained about the system behavior violate the fault independence assumption fault tolerance is based on. This violation may give attackers the opportunity to compromise all replicas simultaneously, in particular if they can mount the attack from already compromised components. In this paper, we analyze vulnerabilities of time-triggered systems, focusing on safety-certified multicore real-time systems. We introduce two runtime mitigation strategies to withstand directed timing inference based attacks: (i) schedule randomization at slot level, and (ii) randomization within a set of offline constructed schedules. We evaluate these mitigation strategies with synthetic experiments and a real case study to show their effectiveness and practicality.
Cite as
Kristin Krüger, Nils Vreman, Richard Pates, Martina Maggio, Marcus Völp, and Gerhard Fohler. Randomization as Mitigation of Directed Timing Inference Based Attacks on Time-Triggered Real-Time Systems with Task Replication. In LITES, Volume 7, Issue 1 (2021): Special Issue on Embedded System Security. Leibniz Transactions on Embedded Systems, Volume 7, Issue 1, pp. 01:1-01:29, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
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@Article{kruger_et_al:LITES.7.1.1,
author = {Kr\"{u}ger, Kristin and Vreman, Nils and Pates, Richard and Maggio, Martina and V\"{o}lp, Marcus and Fohler, Gerhard},
title = {{Randomization as Mitigation of Directed Timing Inference Based Attacks on Time-Triggered Real-Time Systems with Task Replication}},
journal = {Leibniz Transactions on Embedded Systems},
pages = {01:1--01:29},
ISSN = {2199-2002},
year = {2021},
volume = {7},
number = {1},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/LITES.7.1.1},
doi = {10.4230/LITES.7.1.1},
annote = {Keywords: real-time systems, time-triggered systems, security}
}
Document
We know what you're doing! Application detection using thermal data
Abstract
Modern mobile and embedded devices have high computing power which allows them to be used for multiple purposes. Therefore, applications with low security restrictions may execute on the same device as applications handling highly sensitive information. In such a setup, a security risk occurs if it is possible that an application uses system characteristics to gather information about another application on the same device.In this work, we present a method to leak sensitive runtime information by just using temperature sensor readings of a mobile device. We employ a Convolutional-Neural-Network, Long Short-Term Memory units and subsequent label sequence processing to identify the sequence of executed applications over time. To test our hypothesis we collect data from two state-of-the-art smartphones and real user usage patterns. We show an extensive evaluation using laboratory data, where we achieve labelling accuracies up to 90% and negligible timing error. Based on our analysis we state that the thermal information can be used to compromise sensitive user data and increase the vulnerability of mobile devices. A study based on data collected outside of the laboratory opens up various future directions for research.
Cite as
Philipp Miedl, Rehan Ahmed, and Lothar Thiele. We know what you're doing! Application detection using thermal data. In LITES, Volume 7, Issue 1 (2021): Special Issue on Embedded System Security. Leibniz Transactions on Embedded Systems, Volume 7, Issue 1, pp. 02:1-02:28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
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@Article{miedl_et_al:LITES.7.1.2,
author = {Miedl, Philipp and Ahmed, Rehan and Thiele, Lothar},
title = {{We know what you're doing! Application detection using thermal data}},
journal = {Leibniz Transactions on Embedded Systems},
pages = {02:1--02:28},
ISSN = {2199-2002},
year = {2021},
volume = {7},
number = {1},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/LITES.7.1.2},
doi = {10.4230/LITES.7.1.2},
annote = {Keywords: Thermal Monitoring, Side Channel, Data Leak, Sequence Labelling}
}