On Intercept Probability Minimization under Sparse Random Linear Network Coding

Andrea Tassi*, Robert J. Piechocki, Andrew Nix

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)

2 Citations (Scopus)
105 Downloads (Pure)

Abstract

This paper considers a network where a node wishes to transmit a source message to a legitimate receiver in the presence of an eavesdropper. The transmitter secures its transmissions employing a sparse implementation of random linear network coding (RLNC). A tight approximation to the probability of the eavesdropper recovering the source message is provided. The proposed approximation applies to both the cases where transmissions occur without feedback, or where the reliability of the feedback channel is impaired by an eavesdropper jamming the feedback channel. An optimization framework for minimizing the intercept probability by optimizing the sparsity of the RLNC is also presented. Results validate the proposed approximation and quantify the gain provided by our optimization over solutions where non-sparse RLNC is used.

Original languageEnglish
Article number8673872
Pages (from-to)6137-6141
Number of pages5
JournalIEEE Transactions on Vehicular Technology
Volume68
Issue number6
DOIs
Publication statusPublished - 25 Mar 2019

Keywords

  • intercept probability
  • physical layer security
  • secrecy outage probability
  • Sparse random network coding

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