Unmanned aerial vehicles (UAVs) have become extremely popular for both military and civilian applications due to their ease of deployment, cost-effectiveness, high maneuverability, and availability. Both applications, however, need reliable communication for command and control (C2) and/or data transmission. Utilizing commercial cellular networks for drone communication can enable beyond visual line of sight (BVLOS) operation, high data rate transmission, and secure communication. However, deployment of cellular-connected drones over commercial LTE/5G networks still presents various challenges such as sparse coverage outside urban areas, and interference caused to the network as the UAV is visible to many towers. Commercial 5G networks can offer various features for aerial user equipment (UE) far beyond what LTE could provide by taking advantage of mmWave, flexible numerology, slicing, and the capability of applying AI-based solutions. Limited experimental data is available to investigate the operation of aerial UEs over current, without any modification, commercial 5G networks, particularly in suburban and NON-URBAN areas. In this paper, we perform a comprehensive study of drone communications over the existing low-band and mid-band 5G networks in a suburban area for different velocities and elevations, comparing the performance against that of LTE. It is important to acknowledge that the network examined in this research is primarily designed and optimized to meet the requirements of terrestrial users, and may not adequately address the needs of aerial users. This paper not only reports the Key Performance Indicators (KPIs) compared among all combinations of the test cases but also provides recommendations for aerial users to enhance their communication quality by controlling their trajectory.

Key predistribution schemes are promising lightweight solutions to be placed as the cornerstone of key management systems in multihop wireless networks. The intermediate decryption–encryption problem, however, is considered as the security threat of such schemes. Multipath algorithms have been proposed to face such a shortcoming. Alas, these solutions are vulnerable against the node capture attack, where the attacker compromises a fraction of network nodes. In this article, we propose BlocKP, a Blockchain-based solution to increase the resistance of the network against the node capture attack. BlocKP utilizes disjoint key paths for a key-exchange process, where the keying materials form a block at the source side. Each key path step generates the next block of the Blockchain until the keying materials reach the destination. BlocKP is a general framework applicable to any key predistribution schemes. We propose BlocKP in two versions BlocKP-I and BlocKP-II, where the latter enhances the resistance of BlocKP-I using erasure codes at the cost of negligible control traffic. We analytically show that BlocKP improves the resistance of the network against the node capture attack to almost perfect resistance, using just a small number of paths. We evaluate our solution by performing extensive simulations, considering three baseline key predistribution schemes, including probabilistic asymmetric key predistribution (PAKP), strong Steiner trade (SST), and unital key predistribution (UKP). We equipped these schemes with a compatible multipath algorithm to offer end-to-end security. Results show that BlocKP improves the throughput up to 5% and decreases the flow completion time into 20% compared to baseline schemes. It has comparable routing traffic, latency, and throughput with augmented solutions but up to 60% improvement in the resistance against the node capture attack.

The end-to-end throughput of multi-hop communication in wireless ad hoc networks is affected by the conflict between forwarding nodes. It has been shown that sending more packets than maximum achievable end-to-end throughput not only fails to increase throughput but also decreases throughput owing to high contention and collision. Accordingly, it is of crucial importance for a source node to know the maximum end-to-end throughput. The end-to-end throughput depends on multiple factors, such as physical layer limitations, medium access control (MAC) protocol properties, routing policy, and nodes' distribution. There have been many studies on analytical modeling of end-to-end throughput but none of them has taken routing policy and nodes' distribution as well as MAC layer altogether into account. In this paper, the end-to-end throughput with perfect MAC layer is obtained based on routing policy and nodes' distribution in 1-D and 2-D networks. Then, imperfections of IEEE 802.11 protocol are added to the model to obtain precise value. An exhaustive simulation is also made to validate the proposed models using ns-2 simulator. Results show that if the distribution to the next hop for a particular routing policy is known, our methodology can obtain the maximum end-to-end throughput precisely.

Key pre-distribution algorithms have recently emerged as efficient alternatives of key management in today’s secure communications landscape. Secure routing techniques using key pre-distribution algorithms require special algorithms capable of finding optimal secure overlay paths. To the best of our knowledge, the literature of key pre-distribution systems is still facing a major void in proposing optimal overlay routing algorithms. In the literature work, traditional routing algorithms are typically used twice to find a NETWORK layer path from the source node to the destination and then to find required cryptographic paths. In this paper, we model the problem of secure routing using weighted directed graphs and propose a Boolean linear programming (LP) problem to find the optimal path. Albeit the fact that the solutions to Boolean LP problems are of much higher complexities, we propose a method for solving our problem in polynomial time. In order to evaluate its performance and security measures,we apply our proposed algorithm to a number of recently proposed symmetric and asymmetric key pre-distribution methods. The results show that our proposed algorithm offers great network performance improvements as well as security enhancements when augmenting baseline techniques.

Public key management scheme in mobile ad hoc networks (MANETs) is an inevitable solution to achieve different security services such as integrity, confidentiality, authentication and non reputation. Probabilistic asymmetric key pre-distribution (PAKP) is a self-organized and fully distributed approach. It resolves most of MANET's challenging concerns such as storage constraint, limited physical security and dynamic topology. In such a model, secure path between two nodes is composed of one or more random successive direct secure links where intermediate nodes can read, drop or modify packets. This way, intelligent selection of intermediate nodes on a secure path is vital to ensure security and lower traffic volume. In this paper, subjective logic is used to improve PAKP method with the aim to select the most trusted and robust path. Consequently, our approach results in a better data traffic and also improve the security. Proposed algorithm chooses the least number of nodes among the most trustworthy nodes which are able to act as intermediate stations. We exploit two subjective logic based models: one exploits the subjective nature of trust between nodes and the other considers path conditions. We then evaluate our approach using network simulator ns-3. Simulation results confirm the effectiveness and superiority of the proposed protocol compared to the basic PAKP scheme.

Performance evaluation of mobile networks needs accurate simulation set up including realistic characteristics. The most important issue in mobile networks' simulation is the mobility of the nodes. Since mobile nodes usually are carried by humans, thus, nodes mobility should be modelized as human movement. To the best of our knowledge, none of the existing mobility models have the ability to modelize all the human movement characteristics. In this paper, a new mobility model has been proposed based on the human mobility data collected for more than 6000 hours. The new model captures human mobility properties by introducing hotspot zones, using a graph of hotspot zones as the input area map, dividing day time to some periods and modeling various speeds in different times and spaces. Moreover, it models some other important human mobility features that had been modeled in previous works. To evaluate the performance of the proposed model, it is compared with real collected data.

Mobile ad hoc networks (MANETs) have been turned into very attractive area of research in the duration of recent years, whereas security is the most challenging point that they undergo. Cryptography is an essential solution for providing security within MANETs. However, storing all keys in every node, if practically possible, is inefficient in large scale MANETs due to some limitations such as memory or process capability. This paper extends our previous idea which was a novel probabilistic key management algorithm that stores only a few randomly chosen keys instead of all ones. In this paper, several different scenarios are proposed for key selection in which they are more practical, and then, the impact of each scenario on the performance and security metrics is analyzed. Results show that the proposed scenarios can reduce the path length in addition to keeping the network highly connected.