Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Enhancing Physical Layer Security in LEO Satellite-Enabled IoT Network Communications

Anna Talgat, Ruibo Wang, Mustafa A. Kishk, Mohamed-Slim Alouini

TL;DR

This work tackles uplink security in LEO satellite enabled IoT by marrying stochastic geometry with physical layer security techniques. By modeling a multi-tier constellation of legitimate and eavesdropper satellites and employing artificial noise, it derives low-complexity analytical expressions for key security metrics including $P_{av}$, $P_{cov}$, $P_{suc}$, $P_{out}$, and $P_{sec}$. The contribution includes a novel SG-based framework, AN integration, Monte Carlo validation, and actionable design guidance on constellation size, beamwidth, and IoT density to optimize secrecy. The approach offers a scalable, tractable means to assess and enhance security for future large-scale LEO IoT deployments.

Abstract

The extensive deployment of Low Earth Orbit (LEO) satellites introduces significant security challenges for communication security issues in Internet of Things (IoT) networks. With the rising number of satellites potentially acting as eavesdroppers, integrating Physical Layer Security (PLS) into satellite communications has become increasingly critical. However, these studies are facing challenges such as dealing with dynamic topology difficulties, limitations in interference analysis, and the high complexity of performance evaluation. To address these challenges, for the first time, we investigate PLS strategies in satellite communications using the Stochastic Geometry (SG) analytical framework. We consider the uplink communication scenario in an LEO-enabled IoT network, where multi-tier satellites from different operators respectively serve as legitimate receivers and eavesdroppers. In this scenario, we derive low-complexity analytical expressions for the security performance metrics, namely availability probability, successful communication probability, and secure communication probability. By introducing the power allocation parameters, we incorporate the Artificial Noise (AN) technique, which is an important PLS strategy, into this analytical framework and evaluate the gains it brings to secure transmission. In addition to the AN technique, we also analyze the impact of constellation configuration, physical layer parameters, and network layer parameters on the aforementioned metrics.

Enhancing Physical Layer Security in LEO Satellite-Enabled IoT Network Communications

TL;DR

This work tackles uplink security in LEO satellite enabled IoT by marrying stochastic geometry with physical layer security techniques. By modeling a multi-tier constellation of legitimate and eavesdropper satellites and employing artificial noise, it derives low-complexity analytical expressions for key security metrics including , , , , and . The contribution includes a novel SG-based framework, AN integration, Monte Carlo validation, and actionable design guidance on constellation size, beamwidth, and IoT density to optimize secrecy. The approach offers a scalable, tractable means to assess and enhance security for future large-scale LEO IoT deployments.

Abstract

The extensive deployment of Low Earth Orbit (LEO) satellites introduces significant security challenges for communication security issues in Internet of Things (IoT) networks. With the rising number of satellites potentially acting as eavesdroppers, integrating Physical Layer Security (PLS) into satellite communications has become increasingly critical. However, these studies are facing challenges such as dealing with dynamic topology difficulties, limitations in interference analysis, and the high complexity of performance evaluation. To address these challenges, for the first time, we investigate PLS strategies in satellite communications using the Stochastic Geometry (SG) analytical framework. We consider the uplink communication scenario in an LEO-enabled IoT network, where multi-tier satellites from different operators respectively serve as legitimate receivers and eavesdroppers. In this scenario, we derive low-complexity analytical expressions for the security performance metrics, namely availability probability, successful communication probability, and secure communication probability. By introducing the power allocation parameters, we incorporate the Artificial Noise (AN) technique, which is an important PLS strategy, into this analytical framework and evaluate the gains it brings to secure transmission. In addition to the AN technique, we also analyze the impact of constellation configuration, physical layer parameters, and network layer parameters on the aforementioned metrics.
Paper Structure (19 sections, 5 theorems, 32 equations, 8 figures, 2 tables)

This paper contains 19 sections, 5 theorems, 32 equations, 8 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Motivation
  3. PLS Techniques in Satellite Networks
  4. Related Works for Stochastic Geometry
  5. Contribution
  6. System Model
  7. Spatial Distribution Model
  8. Channel Model
  9. Artificial Noise
  10. Performance Analysis
  11. Numerical Results
  12. System Design on Network Availability
  13. Enhancing PLS: Techniques and Trade-offs
  14. Security Performance Optimization
  15. Conclusion
  16. ...and 4 more sections

Key Result

Lemma 1

Given the typical IoT device and the closest satellite within the $m$-th tier, the CDF of the contact angle $\theta_{m,0}$ is given by and the corresponding PDF is where $\theta_{m, \mathrm{max}}$ is defined in (eq: theta_max).

Figures (8)

  • Figure 1: Illustration of the multi-tier architecture of the network, depicting LS and ES at various altitudes. This configuration enables detailed analysis of signal interactions and security measures across d different altitude levels.
  • Figure 2: Illustration of satellite beamwidth $\theta_{\rm beam}$ and its impact on Earth's surface coverage.
  • Figure 3: Heat map representing the $\mathcal{P}_{m, \rm av}$ for different parameters of satellite network.
  • Figure 4: The effects of power allocation across three configurations on $\mathcal{P}_{\rm sec}$.
  • Figure 5: Impact of satellite numbers on $\mathcal{P}_{\rm sec}$ against beam angle.
  • ...and 3 more figures

Theorems & Definitions (8)

  • Lemma 1: Contact Angle Distribution
  • Definition 1
  • Lemma 2: Availability Probability
  • Definition 2
  • Lemma 3: Laplace Transform of Interference
  • Lemma 4: Coverage Probability
  • Definition 3
  • Theorem 1: Secrecy Outage Probability