A New Intrusion Detection Framework for Vehicular Networks
| Affiliation auteurs | !!!! Error affiliation !!!! |
| Titre | A New Intrusion Detection Framework for Vehicular Networks |
| Type de publication | Conference Paper |
| Year of Publication | 2014 |
| Auteurs | Sedjelmaci H, Senouci SMohammed |
| Editor | Jamalipour A, Deng DJ |
| Conference Name | 2014 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC) |
| Publisher | IEEE; IEEE Commun Soc; IEEE, New S Wales Sect |
| Conference Location | 345 E 47TH ST, NEW YORK, NY 10017 USA |
| ISBN Number | 978-1-4799-2003-7 |
| Mots-clés | Attacks, clustering, Data collection, Intrusion detection, vehicular networks |
| Résumé | In this paper, we design and implement a new Intrusion Detection Framework for Vehicular Networks (IDFV). These networks are vulnerable to various security attacks due to the lack of centralized infrastructure. The aim of our framework is then to secure them against the most dangerous routing attacks that have a high severity damage such as selective forwarding, black hole, wormhole, packets duplication and resource exhaustion attacks that can target such networks. IDFV relies on a set of detection and eviction techniques to detect, in a short delay, malicious vehicles with a high accuracy and eject them. Furthermore, IDFV applies a robust reputation schema to evaluate vehicles' trust level. We analyze the performances of our framework using NS-3. Simulation results show that IDFV exhibits a high level of security i.e. high detection rate, low false positive rate and a fast attacks' detection compared to detection frameworks proposed in current literature. |