# Intermittent Jamming against Telemetry and Telecommand of Satellite Systems and A Learning-driven Detection Strategy

arXiv: https://arxiv.org/abs/2107.06181 · HTML: https://mlsanity.com/paper/2107.06181/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 23 references that are in the map.
- First posted on arXiv 10 Jul 2021.

## Builds on (most cited first, 5 of 5)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Deep Learning for Launching and Mitigating Wireless Jamming Attacks](https://mlsanity.com/paper/1807.02567/) (2018)
- [Deep Learning for RF Signal Classification in Unknown and Dynamic Spectrum Environments](https://mlsanity.com/paper/1909.11800/) (2019)
- [Massive MIMO Transmission for LEO Satellite Communications](https://mlsanity.com/paper/2002.08148/) (2020)
- [Location Management in IP-based Future LEO Satellite Networks: A Review](https://mlsanity.com/paper/2101.08336/) (2021)

## Built on by (most cited first, 1 of 1)

- [Integrated Space Domain Awareness and Communication System](https://mlsanity.com/paper/2211.10260/) (2022)

## Abstract (arXiv)

Towards sixth-generation networks (6G), satellite communication systems, especially based on Low Earth Orbit (LEO) networks, become promising due to their unique and comprehensive capabilities. These advantages are accompanied by a variety of challenges such as security vulnerabilities, management of hybrid systems, and high mobility. In this paper, firstly, a security deficiency in the physical layer is addressed with a conceptual framework, considering the cyber-physical nature of the satellite systems, highlighting the potential attacks. Secondly, a learning-driven detection scheme is proposed, and the lightweight convolutional neural network (CNN) is designed. The performance of the designed CNN architecture is compared with a prevalent machine learning algorithm, support vector machine (SVM). The results show that deficiency attacks against the satellite systems can be detected by employing the proposed scheme.