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Physical Layer Security in Finite Blocklength Massive IoT with Randomly Located Eavesdroppers

Tijana Devaja, Milica Petkovic, Sokol Kosta, Dejan Vukobratovic, Cedomir Stefanovic

Abstract

This paper analyzes the physical layer security performance of massive uplink Internet of Things (IoT) networks operating under the finite blocklength (FBL) regime. IoT devices and base stations (BS) are modeled using a stochastic geometry approach, while an eavesdropper is placed at a random location around the transmitting device. This system model captures security risks common in dense IoT deployments. Analytical expressions for the secure success probability, secrecy outage probability and secrecy throughput are derived to characterize how stochastic interference, fading and eavesdropper spatial uncertainty interact with FBL constraints in short packet uplink transmissions. Numerical results illustrate key system behavior under different network and channel conditions.

Physical Layer Security in Finite Blocklength Massive IoT with Randomly Located Eavesdroppers

Abstract

This paper analyzes the physical layer security performance of massive uplink Internet of Things (IoT) networks operating under the finite blocklength (FBL) regime. IoT devices and base stations (BS) are modeled using a stochastic geometry approach, while an eavesdropper is placed at a random location around the transmitting device. This system model captures security risks common in dense IoT deployments. Analytical expressions for the secure success probability, secrecy outage probability and secrecy throughput are derived to characterize how stochastic interference, fading and eavesdropper spatial uncertainty interact with FBL constraints in short packet uplink transmissions. Numerical results illustrate key system behavior under different network and channel conditions.
Paper Structure (17 sections, 28 equations, 4 figures)

This paper contains 17 sections, 28 equations, 4 figures.

Table of Contents

  1. Introduction
  2. System and Channel Model
  3. Network Geometry and Random Access Scheme
  4. Association and Distance Distributions
  5. Eavesdropper Location Model
  6. Signal-to-Interference Ratio (SIR)
  7. Small-Scale Fading Model
  8. Interference Field and Statistics
  9. Finite Blocklength Decoding Model
  10. Block Error Probability at the Legitimate Receiver
  11. Block Error Probability at the Eavesdropper
  12. Secrecy Metrics Under Finite Blocklength
  13. Finite Blocklength Secure Success Probability
  14. Finite Blocklength Secrecy Outage Probability
  15. Secrecy Throughput
  16. ...and 2 more sections

Figures (4)

  • Figure 1: System model.
  • Figure 2: $P_{\mathrm{sec}}$ versus the IoT device density $\lambda_u$ for coding rates $R\in\{1/8,\,1/4\}$, distances $D\in\{20~\rm m,\,50~\rm m, 100~\rm m\}$, with a fixed blocklength $n=128$ and Nakagami parameter $m=1$. BS density is $\lambda_b=10^{-4}$, with activation probability $p = 0.001$.
  • Figure 3: $P_{\mathrm{out}}$ as a function of the BS antenna gain $G_b$ for three BS densities, $\lambda_b\in\{10^{-6},\,10^{-5},\,10^{-4}\}$, and two access probabilities, $p=5\times10^{-2}$ and $p=10^{-2}$. The coding rate is $R=1/4$, distance $D=100$ m, user density $\lambda_u=10^{-3}$, blocklength $n=128$, and Nakagami parameter $m=4$.
  • Figure 4: $T_{\mathrm{sec}}$ as a function of the access probability $p$, blocklengt $n=512$, and four BS densities, $\lambda_b\in\{10^{-6},10^{-5},10^{-4},10^{-3}\}$, rate $R=1/8$, distance $D=150$ m, user density $\lambda_u=10^{-3}$ and parameter $m=2$.