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RACE: Risk analysis for cooperative engines

Authors: Aymen Boudguiga; Antoine Boulanger; Pascal Chiron; Witold Klaudel; Houda Labiod; Jean-Christophe Seguy;

RACE: Risk analysis for cooperative engines

Abstract

Nowadays, Cooperative Intelligent Transport Systems (C-ITS) are not fiction anymore. Prototypes of self-driving vehicles are flourishing everywhere, e.g. Google driverless car. These new generation vehicles are not only intelligent as they do not need human intervention during cruise, but they also communicate together creating a cooperative network. However, C-ITS are becoming the prey of hackers and the target of cyberattacks. Consequently, a reliable risk analysis method needs to be defined to prevent C-ITS threats and to assess their vulnerabilities. In this paper, we define a simple and efficient risk analysis method called RACE. We compare it to two of main risk analysis methods, namely TVRA and EVITA.

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    influence
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Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
19
Top 10%
Top 10%
Average
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