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Secure and scalable rerouting in LEO satellite networks

Abstract:
Resilient routing in large-scale Low Earth Orbit (LEO) satellite networks remains a key challenge due to frequent and unpredictable link and node failures, potentially in response to cybersecurity breaches. While prior work has explored rerouting strategies with various levels of network awareness, their relative tradeoffs under dynamic failure conditions remain underexplored.
In this work, we extend the Deep Space Network Simulator (DSNS) to systematically compare three rerouting paradigms, each differing in the scope of failure knowledge available to each node. We compare local neighbor-based, segment-based and global-knowledge-based rerouting as well as a naive source routing solution that is unaware of failures.
Our main goal is to evaluate how the breadth of failure awareness impacts routing performance and resilience under failures, both random and targeted. We measure delivery ratio, latency, rerouting overhead, and loop occurrence. Our findings show the potential of segment-based rerouting to achieve a favorable tradeoff between local responsiveness and global coordination, offering resilience benefits with minimal overhead—insights that can inform future fault-tolerant satellite network design.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.14722/spacesec.2026.23075

Authors

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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Oxford college:
St Anne's College
Role:
Author
ORCID:
0000-0003-2200-1066


Publisher:
Internet Society
Host title:
Proceedings: SpaceSec 2026
Article number:
75
Publication date:
2026-02-23
Acceptance date:
2025-12-14
Event title:
4th Workshop on Security of Space and Satellite Systems (SpaceSec)
Event series:
NDSS Symposium 2026
Event location:
San Diego, California
Event website:
https://spacesec.info/
Event start date:
2026-02-23
Event end date:
2026-02-23
DOI:
EISBN:
9781970672022


Language:
English
Subtype:
Poster
Pubs id:
2372020
Local pid:
pubs:2372020
Deposit date:
2026-02-13
ARK identifier:

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