Title :
RACE: Risk analysis for cooperative engines
Author :
Aymen Boudguiga;Antoine Boulanger;Pascal Chiron;Witold Klaudel;Houda Labiod;Jean-Christophe Seguy
Author_Institution :
IRT SystemX, 8 avenue de la Vauve 91120-Palaiseau
fDate :
7/1/2015 12:00:00 AM
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.
Keywords :
"Vehicles","Security","Risk analysis","Safety","Artificial intelligence","Automotive engineering","Engines"
Conference_Titel :
New Technologies, Mobility and Security (NTMS), 2015 7th International Conference on
DOI :
10.1109/NTMS.2015.7266516