Name
Abstract | ||
|---|---|---|
Wireless radio channels are known to contain information about the surrounding propagation environment, which can be extracted using established wireless sensing methods. Thus, today's ubiquitous wireless devices are attractive targets for passive eavesdroppers to launch reconnaissance attacks. In particular, by overhearing standard communication signals, eavesdroppers obtain estimations of wireless channels which can give away sensitive information about indoor environments. For instance, by applying simple statistical methods, adversaries can infer human motion from wireless channel observations, allowing to remotely monitor premises of victims. In this work, building on the advent of intelligent reflecting surfaces (IRSs), we propose IRShield as a novel countermeasure against adversarial wireless sensing. IRShield is designed as a plug-and-play privacy-preserving extension to existing wireless networks. At the core of IRShield, we design an IRS configuration algorithm to obfuscate wireless channels. We validate the effectiveness with extensive experimental evaluations. In a state-of-the-art human motion detection attack using off-the-shelf Wi-Fi devices, IRShield lowered detection rates to 5% or less. |
Year | Venue | DocType |
|---|---|---|
2021 | IACR Cryptology ePrint Archive | Journal |
Volume | Citations | PageRank |
2021 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paul Staat | 1 | 0 | 0.68 |
| Simon Mulzer | 2 | 0 | 0.34 |
| Stefan Roth | 3 | 0 | 1.35 |
| Veelasha Moonsamy | 4 | 0 | 0.68 |
| Aydin Sezgin | 5 | 596 | 75.27 |
| Christof Paar | 6 | 3794 | 442.62 |