Analysis and detection of routing attacks on flying ad hoc networks

Unmanned Aerial Vehicles (UAV) are widely used in a variety of fields, especially in military and industrial applications. However, the usage of a single UAV has begun to be insufficient in most missions. In such cases, Flying Ad Hoc Networks (FANETs) that allow more than one UAV to participate in a common network and execute complex tasks in an organized manner is recommended. However, FANETS are target of attacks due to being used in critical applications. Moreover, they are vulnerable to a variety of attacks due to their very nature and the cooperative routing protocols they use. Moreover, FANETs requires new security solutions or adaptation of existing security solutions of Mobile Ad Hoc Networks (MANETs), since it has much higher mobility than MANETs. Since mobility could affect security in different ways, at first attacks against FANETs should be analyzed. This is the main aim of this study. In this paper, various attacks against FANETs, namely dropping, blackhole, sinkhole, flooding attacks are analyzed. This is the first study that presents a comprehensive attack analysis in FANETs by simulating realistic network scenarios, where UAVs move in 3D as in real life. In addition, a dataset is created as a result of this study. The dataset is collected by running various network simulations (with and without attack). Afterwards, using this dataset, the application of artificial neural networks to detect attacks against FANETs is investigated. The results show that the proposed method can successfully detect different types of attacks.