Novel cross layer detection schemes to detect blackhole attack against QoS-OLSR protocol in VANET

In this paper, we propose novel cross-layer cooperative schemes for detecting blackhole attack that commonly targets the quality of service secure optimized link state routing protocol (QoS-OLSR) in vehicular ad-hoc networks (VANETs). The QoS-OLSR relies mainly on the multi-point relays (MPRs) that are responsible for establishing the routing among the nodes in the network. Such nodes are victims of the well known attack named as blackhole where packets are intentionally dropped to cause a denial of service. In the literature, watchdogs are used to detect such an attack by utilizing the captured network layer information. Improving the detection performance of such a technique and minimizing the drawbacks due to the high channel collision are the main goals of this work. As a solution, we propose two detection schemes that allow the information to be exchanged across two and three layers respectively. The first scheme utilizes the information among physical and network layers, while the second one relies on the physical, MAC and network layers to enable an efficient and reliable detection. In the physical layer detection technique, each legitimate user is assigned a signature key that is multiplied by the message, and each monitoring node uses the maximum likelihood approach to determine whether the message is legitimate or not. On the other hand, the MAC detection technique monitors the number of RTS/CTS (request to send/clear to send) requests among all the neighbors while the cooperative watchdog technique is implemented at the network layer to overhear the transmitted exchanged packets among the neighbors. Simulation results are conducted to show that utilizing a cooperative cross layer design enhances the detection rate and minimizes the false alarm rate compared to other contemporary state-of-the-art detection schemes.