Abstract
C-ITS (Cooperative Intelligent Transport Systems) provide nowadays a very huge amounts of data from different sources: vehicles, roadside units, operator servers, smartphone applications. These amounts of data can be exploited and analysed in order to extract pertinent information as driver profiles, abnormal driving behaviours, etc. In this paper, we present a methodology for analysis of data provided by a real experimentation of a cooperative intelligent transport system (C-ITS). We have analysed mainly security issues as privacy, authenticity. We have used unsupervised machine learning approaches. The obtained results have shown interesting results in terms of latency, packet delivery ratio.
Partially supported by The InterCor project number INEA/CEF/TRAN/M2015/1143833.
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Leblanc, B., Bourdy, E., Fouchal, H., de Runz, C., Ercan, S. (2019). Towards Analysing Cooperative Intelligent Transport System Security Data. In: Renault, É., Mühlethaler, P., Boumerdassi, S. (eds) Machine Learning for Networking. MLN 2018. Lecture Notes in Computer Science(), vol 11407. Springer, Cham. https://doi.org/10.1007/978-3-030-19945-6_2
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DOI: https://doi.org/10.1007/978-3-030-19945-6_2
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