Orbital Operations Safety

Sgobba, Tommaso; Allahdadi, Firooz A.

doi:10.1016/b978-0-08-096921-3.00008-8

Cited by 5 publications

(3 citation statements)

References 42 publications

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“…The SSN comprises more than 20 locations, leveraging the US military's extensive network of forward deployed military installations to achieve geographic distribution. It is believed to be the only system capable of tracking smaller objects measuring 5-10 cm in LEO and 1 m in GSO [28,45].…”

Section: Ssa In Practicementioning

confidence: 99%

“…The closest competitor is the Russian Space Surveillance System (RSSS). Its nature and capabilities are opaque, but it is believed to consist of at least 8 sensing sites (primarily within former USSR territory) and to have a catalog about 1/3rd the size of the US SSN [45]. A nominally civilian network -the International Scientific Optical Network (ISON) -is managed by the Russian Academy of Sciences and includes some smaller academic research installations [21].…”

Section: Ssa In Practicementioning

confidence: 99%

“…A handful of smaller networks exist, including the European Space Agency's (ESA) Space Surveillance and Tracking program, and systems operated by China, Canada, India, Japan, Korea, France, and Ukraine [45,54] This data standard was developed in the 1970's to facilitate the sharing of an object's ephemeris (its projected orbital path and position) using two 80-column punch cards [20]. TLEs were designed in conjunction with orbital propagation models to forecast the motion of an object through orbit.…”

Section: Ssa In Practicementioning

confidence: 99%

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On Detecting Deception in Space Situational Awareness

Pavur

Martinovic

2021

Proceedings of the 2021 ACM Asia Conference on Computer and Communications Security

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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.

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Section: Ssa In Practicementioning

confidence: 99%

Section: Ssa In Practicementioning

confidence: 99%

Section: Ssa In Practicementioning

confidence: 99%

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