Denial of service attacks can disrupt beam allocation in LEO satellites
Denial of Service Attacks on Beam Allocation in Large LEO Constellations
Networking and Internet ArchitectureCryptography and Security
Summary
Large groups of satellites in low Earth orbit help provide internet and communication services by directing beams to users on the ground. The authors show that attackers can overload these systems by pretending to demand more service than they actually need, disrupting connections for real users. Different ways of sharing beam capacity and assigning users to beams affect how vulnerable the system is to these attacks. Some methods protect better but may reduce overall performance before attacks happen.
What this means in practice
- •For satellite network operators: Design beam allocation and capacity sharing methods to reduce denial-of-service risks in large LEO constellations.
- •For telecommunication security teams: Develop strategies to detect and mitigate fake user demand that can disrupt satellite communication service quality.
Authors
Ali Abbasi, Pasha Barahimi, Marco Paolieri, Leana Golubchik
Abstract
We study the vulnerability of beam allocation approaches in large low-Earth-orbit (LEO) satellite constellations to adversarial demand inflation resulting in denial-of-service attacks. We consider an attack model in which an adversary places (injects) additional terminals and evaluate these attacks against greedy and max-min-fair beam allocation algorithms, each combined with either equal or demand-proportional intra-cell capacity sharing. Vulnerability is measured using mean demand satisfaction, coverage, and the fraction of legitimate users receiving at least a threshold fraction of their requested capacity under several attack heuristics. There is a trade-off for the system between robustness and performance, meaning the algorithm with the most vulnerability to the attacks (greedy-proportional) has the highest performance before the attacks. Demand-proportional sharing increases the fraction of under-served users up to 34% under both allocation algorithms, whereas equal sharing limits the increase up to 13%. The sharing rule also changes the most damaging attack allocation in nearly all cases: demand-proportional sharing rewards concentrating injected terminals in the most loaded cells, while equal sharing performs better when distributing these terminals across the least loaded cells. Furthermore, the max-min-fair beam allocation algorithm forces the attacker to use a higher number of targeted cells to result in extensive damage to the system.