Abstract
Estimation of transmission rates by a malicious user can serve as a stepping stone to further attacks on the network. In this paper, we aim to investigate the general problem of estimating traffic transmission rates in a CSMA/CA network using a class of passive eavesdropping methods. We consider the case where a single eavesdropper passively monitors all active network nodes but cannot observe all packet transmissions due to spatial-reuse collisions. To enable tractable analysis, we first propose an approximate statistical model that can help the eavesdropper estimate transmission rates with partial measurements under spatial reuse. We next consider a class of eavesdroppers that become increasingly more capable, and develop a framework to demonstrate that two classes of eavesdropper capabilities are sufficient to achieve a consistent transmission rate estimator. We provide numerical tests of our proposed estimators under practical network cases using the NS-3 simulator that validate the theoretical results.
Original language | English (US) |
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Pages (from-to) | 9793-9807 |
Number of pages | 15 |
Journal | IEEE Transactions on Wireless Communications |
Volume | 22 |
Issue number | 12 |
DOIs | |
State | Published - Dec 1 2023 |
Keywords
- CSMA/CA
- Ergodic theorem
- IEEE80211
- Internet of Things (IoT)
- RF fingerprinting
- eavesdropping
- network spatial reuse
- statistical traffic analysis
- stochastic process
- wireless security
ASJC Scopus subject areas
- Computer Science Applications
- Electrical and Electronic Engineering
- Applied Mathematics