Filling the gap between automotive systems, safety, and software engineering

Macher, Georg; Stolz, Michael; Armengaud, Eric; Kreiner, Christian

doi:10.1007/s00502-015-0301-x

Cited by 9 publications

(3 citation statements)

References 9 publications

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“…Security has been taken into account in the early phases of the development cycle of automotive electronics systems, both by enforcing software programming standards that prevent software defects that may enable cyber-attacks [15], as well as by implementing security mechanisms for secure communication [24,25], including software delivery, installation and flashing [1,35]. Factors like Required Resources and Required Know-How have been considered in the SAHARA (Security-Aware Hazard Analysis and Risk Assessment) method for defining threats criticality [27].…”

Section: Securitymentioning

confidence: 99%

Verifying data secure flow in AUTOSAR models

Bernardeschi

Natale

Dini

et al. 2018

J Comput Virol Hack Tech

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This paper presents an approach for enhancing the design phase of AUTOSAR models when security annotations are required. The approach is based on information flow analysis and abstract interpretation. The analysis evaluates the correctness of the model by assessing if the flow of data is secure with respect to causal data dependencies within the model. To find these dependencies an exhaustive search through the model would be required. Abstract interpretation is used as a trade-off between the precision and complexity of the analysis. The approach also provides annotated models without oversizing the set of annotations.

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Section: Securitymentioning

confidence: 99%

Verifying data secure flow in AUTOSAR models

Bernardeschi

Natale

Dini

et al. 2018

J Comput Virol Hack Tech

View full text Add to dashboard Cite

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“…Moreover, current premium cars implement more than 90 Electronic Control Units (ECU) with close to 1 Gigabyte embedded software code [236]. In 2018, 30% of the overall vehicle cost is predicted to stem from vehicle electronics [237]. The independence of different applications (with different criticality levels) running on the same platform must be made evident.…”

Section: Sensorsmentioning

confidence: 99%

Driver Distraction Using Visual-Based Sensors and Algorithms

Fernández¹,

Usamentiaga

Carús³

et al. 2016

Sensors

105

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Driver distraction, defined as the diversion of attention away from activities critical for safe driving toward a competing activity, is increasingly recognized as a significant source of injuries and fatalities on the roadway. Additionally, the trend towards increasing the use of in-vehicle information systems is critical because they induce visual, biomechanical and cognitive distraction and may affect driving performance in qualitatively different ways. Non-intrusive methods are strongly preferred for monitoring distraction, and vision-based systems have appeared to be attractive for both drivers and researchers. Biomechanical, visual and cognitive distractions are the most commonly detected types in video-based algorithms. Many distraction detection systems only use a single visual cue and therefore, they may be easily disturbed when occlusion or illumination changes appear. Moreover, the combination of these visual cues is a key and challenging aspect in the development of robust distraction detection systems. These visual cues can be extracted mainly by using face monitoring systems but they should be completed with more visual cues (e.g., hands or body information) or even, distraction detection from specific actions (e.g., phone usage). Additionally, these algorithms should be included in an embedded device or system inside a car. This is not a trivial task and several requirements must be taken into account: reliability, real-time performance, low cost, small size, low power consumption, flexibility and short time-to-market. The key points for the development and implementation of sensors to carry out the detection of distraction will also be reviewed. This paper shows a review of the role of computer vision technology applied to the development of monitoring systems to detect distraction. Some key points considered as both future work and challenges ahead yet to be solved will also be addressed.

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“…The authors of (Macher, Stolz, Armengaud, and Kreiner 2015) aimed at achieving consistency of information between several tools involved in the development process, through to a single source of information principle. In the goal of achieving dependability (safety, security) in the development process between different teams and stakeholders, they decided against a document-centric approach and used the capabilities of UML and SysML for their design.…”

Section: Related Workmentioning

confidence: 99%

SaVeSoC - Safety Aware Virtual Prototype Generation and Evaluation of a System On Chip

2017

Model-Driven Approaches for Simulation Engineering (Mod4Sim 2017)

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The electrification of today's vehicles and the high amount of new assistance features imply more and more complex systems. The sensing and controlling of these systems is the work of the highly distributed and connected electronic control units. To keep pace with the fast growing automotive market, reusability of components and features is today the key to reduce costs and time-to-market. Especially when systems are safety-critical and demand reliability, new methods and tools are thus essential to support the reusability aspect in the development process. A model-based approach, in conjunction, moreover helps to communicate between different stakeholders, provides different views and serves as a central storage of information. Through applying reliability analysis and simulation-based verification methods on our hardware model and furthermore automatic generation of a first virtual prototype, we are able to reduce the tools involved, thus resulting in correctness, completeness and consistency of the entire system.

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Filling the gap between automotive systems, safety, and software engineering

Cited by 9 publications

References 9 publications

Verifying data secure flow in AUTOSAR models

Verifying data secure flow in AUTOSAR models

Driver Distraction Using Visual-Based Sensors and Algorithms

SaVeSoC - Safety Aware Virtual Prototype Generation and Evaluation of a System On Chip

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