# Efficient Security Scheme for Disaster Surveillance UAV Communication Networks
## 2 Related Work  
The UAV systems face many communication challenges due to the drones' intermittent connections so that it is hard to maintain an end-to-end path to destination. Consequently, the UAV network should be a disruption tolerant; information should reach the destination even after some delay and even if the created path to the destination has some fluctuations [10]. The UAVs can be utilized as micro-scale mobile relays to enhance the cellular network performance [11] or as unmanned aerial base stations in mission-critical public safety communications [12]. A simple short horizon algorithm [13] plans dedicated paths for UAVs so that all locations are scanned frequently, at the same time, the optimal UAV speed to achieve the best network throughput and energy constraints is preserved. A fly-hover-and-communicate protocol [14] partitions the ground terminals into disjoint clusters with directional antenna UAV that hovers above the cluster center. The quality of the communication link between UAV and ground nodes is impacted by frequent occlusions in the urban environment so that Ref. [15] combines a Gaussian Process learning approach with relay trajectory planner to predict the strength of the UAV communication relay missions. In Ref. [16], [PERSON] et al. propose a distributed multi-layer UAV (DAMU) 5G wireless network considering different types of UAV designs and the corresponding 5G application scenarios. In Ref. [17], [PERSON] et al. study the LTE connectivity for low altitude small UAVs; it offers wide-area high speed, and secure wireless connectivity, which can enhance control and safety of UAV operations and enable beyond visual line-of-sight (LOS) use cases. In Ref. [18], UAV communications utilize proactive caching of the ground nodes to store the collected readings which can be retrieved anytime from the node's local cache or its nearest neighbor via device-to-device (D2D) communications. An efficient cell-based allocations approach [19] provides the optimal UAV positioning for full coverage in 5G networks while optimizing the throughput coverage.  
However, cellular network connectivity can not be guaranteed in disaster areas and it also comes with high cost. For that reason, Wi-Fi technology deserves to be considered as well. Wi-Fi can provide low cost and high performance user interface [20]. On the other hand, classical Wi-Fi suffers from high contention and short-range communications which result in high multi-hop latency [21] and opens avenue for synchronization attacks [22]. Fortunately, recent standard IEEE 802.11 ah extends the transmission range of Wi-Fi and offers support for relaying [8; 9].  
Only few research works discuss the security aspects of UAV networks. In Ref. [23], [PERSON] and [PERSON] introduce various security and privacy concerns for UAV systems. According to Ref. [24], the authors propose a physical layer security solution to protect the UAV communication systems against eavesdropping and malicious jamming. The solution is based on combining artificial noise with the transmitted information to protect the transmitted data and to confuse the attacker. An inferred context-free grammar method [25] validates the UAV commands by comparing them with the assigned command's format, and consequently alleviates the impact of jamming and hijacking attacks. The coagulation attack that attempts to fully control the UAV by alternating the UAV physical configurations, modifying its waypoint to cause collision, or UAV hijacking is introduced in [26]. While [PERSON] et al. [27] present the securing context information scheme that supports the 3D localization of drones in urban scenarios.