← 研踪 PaperTrailarXiv:2610.34631 · v1
Denial of Service Attacks on Beam Allocation in Large LEO Constellations
首次提交 2026-10-26 07:08
版本更新 2026-10-26 07:08
雷达观测 2026-10-29 00:36
摘要
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.
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v1 · 2026-10-26 07:08 · 最新观测版本
Denial of Service Attacks on Beam Allocation in Large LEO Constellations
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.
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