Conference item
On detecting deception in space situational awareness
- Abstract:
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Space Situational Awareness (SSA) data is critical to the safe piloting of satellites through an ever-growing field of orbital debris. However, measurement complexity means that most satellite operators cannot independently acquire SSA data and must rely on a handful of centralized repositories operated by major space powers. As interstate competition in orbit increases, so does the threat of attacks abusing these information-sharing relationships. This paper offers one of the first considerations of defense techniques against SSA deceptions. Building on historical precedent and real-world SSA data, we simulate an attack whereby an SSA operator seeks to disguise spy satellites as pieces of debris. We further develop and evaluate a machine-learning based anomaly detection tool which allows defenders to detect 90-98% of deception attempts with little to no in-house astrometry hardware.
Beyond the direct contribution of this system, the paper takes a unique interdisciplinary approach, drawing connections between cyber-security, astrophysics, and international security studies. It presents the general case that systems security methods can tackle many novel and complex problems in an historically neglected domain and provides methods and techniques for doing so.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 966.3KB, Terms of use)
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- Publisher copy:
- 10.1145/3433210.3453081
Authors
- Publisher:
- Association for Computing Machinery
- Host title:
- ASIA CCS '21: Proceedings of the 2021 ACM Asia Conference on Computer and Communications Security
- Pages:
- 280–291
- Publication date:
- 2021-05-24
- Acceptance date:
- 2021-03-16
- Event title:
- 16th ACM ASIA Conference on Computer and Communications Security (ACM ASIACCS 2021)
- Event location:
- Virtual event
- Event website:
- https://asiaccs2021.comp.polyu.edu.hk/
- Event start date:
- 2021-06-07
- Event end date:
- 2021-06-11
- DOI:
- ISBN:
- 9781450382878
- Language:
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English
- Keywords:
- Pubs id:
-
1168242
- Local pid:
-
pubs:1168242
- Deposit date:
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2021-03-16
- ARK identifier:
Terms of use
- Copyright holder:
- Pavur and Martinovic
- Copyright date:
- 2021
- Rights statement:
- © 2021 Copyright held by the owner/author(s). Publication rights licensed to ACM.
- Notes:
- This paper was presented at the 16th ACM ASIA Conference on Computer and Communications Security (ACM ASIACCS 2021), 7-11 June 2021, Virtual event. This is the accepted manuscript version of the paper. The final version is available online from the Association for Computing Machinery at: https://doi.org/10.1145/3433210.3453081
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