# Random Routing Algorithm for Enhancing the Cybersecurity of LEO Satellite Networks
## 1 Introduction
They also consider how the knowledge of the relative position of each satellite in the grid may be beneficial to forwarding NDN packets. Another challenge is presented in the form of the topology of the network as shown in [19]; the authors show that network topology has a big impact on the type of routing algorithm that should be used, e.g., Delay-Tolerant Network (DTN) or non-Delay-Tolerant Network (non-DTN). The routing strategy in such a dynamic network will depend on the density of the network and the mobility pattern. As the density of nodes increases, the probability of finding the paths increases and hence the Non-Delay-Tolerant Network (Non-DTN) is more suitable for enhancing the performance of routing protocols. The Delay Tolerant Network (DTN) protocols are more favorable in the case of low density and high mobility [19]. In [20], the authors offer a realistic uplink framework designed to imitate real satellite network performance issues such as satellite availability, packet collision, and interference. This implies that those are actual challenges that routing protocols try to mitigate. The capacity of the ground-to-satellite link is another major challenge, being subject to various atmospheric fading mechanisms that cause it to be a bottleneck of the entire network. Some challenges of routing algorithms in LEO satellite networks arise from unbalanced traffic distribution among the nodes of the network, which may lead to surges of activities in some areas. This is studied in [21] using a two-hops state-aware routing strategy based on deep reinforcement learning (DRL-THSA). The key factors that cause LSNs to be more vulnerable to attacks compared to terrestrial networks include: (a) satellite locations are largely available to the public and are therefore easier for an adversary to specifically target, (b) low latency requirements limit different path options and cause routing to be more predictable, and (c) their reliance on the cyber networks and the Internet for functioning. However, some other factors that work in the favor of LSNs are: (a) the ever-changing nature of inter-satellite networks that cause the attacker a risk of two attacks congesting each other rather than the target inter-satellite link and (b), as the number of end users connected to the satellite will be much smaller than the Internet, it requires on the part of the adversary a very efficient, careful, and planned use of resources for DDoS attacks. Broadly, the solution to the cyberattacks can be categorized into two types: (a) Physical layer solution and (b) cryptography-based solutions. The physical layer solution takes advantage of the the physical properties of the channel and wave propagation to secure the network against the eavesdropper while the cryptographic solution utilizes the encryption algorithms. Some of the works that focus on physical layer solutions are as follows. In [22], the authors have investigated the eavesdropping in Non-Geostationary Orbit (NGSO) communication systems in the physical layer and derived the closed form expression for channel secret capacity and outage probability while considering the effect of rain attenuation. In [23], the authors have investigated the secrecy performance of a land mobile satellite channel with shadowed-Rician fading. An attempt to solve the confidentiality problem in the network coding of multi-beam satellite systems has been studied and, using semi-definite programming, the sum secrecy rate was optimized by designing optimal beamforming [24]. In [25], the authors have minimized the total transmit power of a satellite while satisfying the user's secrecy rate for a scenario in which the legitimate receivers are placed among multiple beams while being surrounded by many passive eavesdroppers. The investigation of the secrecy outage probability of a hybrid satellite-terrestrial relay network (HSTRN) in the presence of multiple eavesdroppers is studied in [26].