Abstract:
Unmanned Aerial Vehicles (UAVs) are gradually becoming more widely used across a wide range of real-world applications because of their rapid and cost-effective deployment. A UAV networks is the wireless and ad-hoc networks which facilitate from UAV to UAV and from UAV to the GC. However, it is due to the exchange of information over a wireless channel. UAVs are exposed to cyber-attacks and threats. If an UAV is compromised by the attacker, then the whole network can be compromised by the command of an attacker. He can spread false information over the network. The BRUIDS scheme relies on the rule base detection to detect the attacker. our research proposed rule base detection and anomaly the detection technique to achieve the high detection of accuracy, we will in this design and to implement a Hierarchical and Intrusion Detection and a Response Scheme (HIDRS), That will operate at the UAV and the GC level, by detect the malicious anomaly which threatened a network. In our scheme, an SVM base anomaly detection technique to verify an attack which is detected by the UAV agent and to categorize into a list (malicious, suspect, and normal). In this research, we focused on the most dangerous cyber-attack that may target the UAV networks, which are GPS spoofing, black hole, and grey hole attack. Our best simulation confirms that the scheme which we proposed is performed efficiently in-term of the attack detection and even with the high numbers of the UAVs and the attacker since it shows, a low number of false positive and the detection rate (DR) is high.
