HYDRA: Unearthing"Black Swan"Vulnerabilities in LEO Satellite Networks

2026-02-06

AI Summary

Traditional topological centrality measures struggle to capture systemic “black swan” risks in low Earth orbit satellite networks arising from dynamic load imbalances and higher-order dependencies. This work proposes the HYDRA framework, which, for the first time, models the network’s dynamic dependency structure using hypergraphs and introduces Hypergraph Betweenness Centrality (HBC) to quantify a node’s structural criticality in balancing load and redundancy. Simulations integrating real Starlink orbital data with a population gravity model demonstrate that HBC substantially outperforms conventional metrics in precisely identifying latent, high-impact nodes whose failure can trigger network-wide cascading failures. Notably, these critical nodes cluster at topological peripheries—such as space-to-ground interfaces—rather than core satellites, revealing the decisive role of peripheral structural stress in system resilience and advocating a paradigm shift in security design from mere connectivity to structural stress awareness.

Technology Category

• Data Mining & Knowledge Management: Graph Mining, Social Network Analysis & Community
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Constraint Satisfaction and Optimization: Satisfiability

Application Category

• Graph Algorithms and Modeling for the Web: Foundation models and LLMs for Web-related graphs
• Social Networks and Social Media: Social media analysis through the lenses of networks
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

As Low Earth Orbit (LEO) become mega-constellations critical infrastructure, attacks targeting them have grown in number and range. The security analysis of LEO constellations faces a fundamental paradigm gap: traditional topology-centric methods fail to capture systemic risks arising from dynamic load imbalances and high-order dependencies, which can transform localized failures into network-wide cascades. To address this, we propose HYDRA, a hypergraph-based dynamic risk analysis framework. Its core is a novel metric, Hyper-Bridge Centrality (HBC), which quantifies node criticality via a load-to-redundancy ratio within dependency structures. A primary challenge to resilience: the most critical vulnerabilities are not in the densely connected satellite core, but in the seemingly marginal ground-space interfaces. These are the system's"Black Swan"nodes--topologically peripheral yet structurally lethal. We validate this through extensive simulations using realistic StarLink TLE data and population-based gravity model. Experiments demonstrate that HBC consistently outperforms traditional metrics, identifying critical failure points that surpass the structural damage potential of even betweenness centrality. This work shifts the security paradigm from connectivity to structural stress, demonstrating that securing the network edge is paramount and necessitates a fundamental redesign of redundancy strategies.

Problem

• LEO satellite networks
• Black Swan vulnerabilities
• systemic risk
• cascading failures
• ground-space interfaces

Innovation

• Hypergraph-based analysis
• Hyper-Bridge Centrality
• Black Swan vulnerabilities
• LEO satellite networks
• Structural stress