Published November 26, 2023 | Version 1.0.0
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Model Weights for "Watch This Space: Securing Satellite Communication through Resilient Transmitter Fingerprinting"

Description

Model weights for use with the SatIQ fingerprinting models used in the paper “Watch This Space: Securing Satellite Communication through Resilient Transmitter Fingerprinting”. The models are used to authenticate Iridium satellites from high sample rate message headers.

The data collection and model code can be found at the following URL: https://github.com/ssloxford/SatIQ

The preprint is available on arXiv at the following URL: https://arxiv.org/abs/2305.06947

The final trained model is ae-triplet-final.h5. The others are from the additional experiments and analyses described in the paper, and are included for completeness.

When using this data, please cite the following paper: “Watch This Space: Securing Satellite Communication through Resilient Transmitter Fingerprinting”. The BibTeX entry is given below:

@inproceedings{smailesWatch2023,
  author = {Smailes, Joshua and K{\"o}hler, Sebastian and Birnbach, Simon and Strohmeier, Martin and Martinovic, Ivan},
  title = {{Watch This Space}: {Securing Satellite Communication through Resilient Transmitter Fingerprinting}},
  year = {2023},
  publisher = {Association for Computing Machinery},
  booktitle = {Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security},
  location = {Copenhagen, Denmark},
  series = {CCS '23}
}

 

Files

Files (1.4 GB)

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md5:e40d715441dc1241dc43b4bfdaf573f5
120.6 MB Download
md5:1d75167c0a58666cf4097519b0e772f7
120.6 MB Download
md5:0d584d7daeb1b3b892555616c369ec10
120.6 MB Download
md5:786a6d57c7107b3da3d06363b643e990
120.6 MB Download
md5:c0178328799a137c06f58d70a42e90c3
120.6 MB Download
md5:cbc3dd0eaa60f4ec7e2acf332901074b
120.6 MB Download
md5:7831881d05b0b0701ccab6fc075b65b6
120.6 MB Download
md5:ecaa8ba486f1953baccda1e7cdc5c5a8
120.6 MB Download
md5:969ceff287ccb912913f83eac75d0863
120.6 MB Download
md5:88efd6b5cf71532676542e0ab707a582
120.6 MB Download
md5:7ebb0026baebdda223b3c67860f874a7
120.6 MB Download
md5:ff20d6add1c134f583b3ba03c272c38f
60.3 MB Download

Additional details

Related works

Is supplement to
Dataset: 10.5281/zenodo.8220494 (DOI)
Preprint: 10.48550/arXiv.2305.06947 (DOI)