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---WiFi Vision: X-Ray Vision using ambient WiFi signals now possible---
“X-Ray Vision” using WiFi signals isn’t new, though previous methods required knowledge of specific WiFi transmitter placements and connection to the network in question. These limitations made WiFi vision an unlikely security breach, until now.
Cybersecurity researchers at the University of California and University of Chicago have succeeded in detecting the presence and movement of human targets using only ambient WiFi signals and a smartphone.
The researchers designed and implemented a 2-step attack: the 1st step uses statistical data mining from standard off-the-shelf smartphone WiFi detection to “sniff” out WiFi transmitter placements. The 2nd step involves placement of a WiFi sniffer to continuously monitor WiFi transmissions.
Three proposed defenses to the WiFi vision attack are Geofencing, WiFi rate limiting, and signal obfuscation.
Geofencing, or reducing the spatial range of WiFi devices, is a great defense against the attack. For its advantages, however, geofencing is impractical and unlikely to be adopted by most, as the simplest geofencing tactic would also heavily degrade WiFi connectivity.
WiFi rate limiting is effective against the 2nd step attack, but not against the 1st step attack. This is a simple defense to implement, but because of the ubiquity of IoT devices, it is unlikely to be widely adopted as it would reduce the usability of such devices.
Signal obfuscation adds noise to WiFi signals, effectively neutralizing the attack. This is the most user-friendly of all proposed defenses, with minimal impact to user WiFi devices. The biggest drawback to this tactic is the increased bandwidth of WiFi consumption, though compared to the downsides of the other mentioned defenses, signal obfuscation remains the most likely to be widely adopted and optimized for this kind of attack.
For more info, please see journal article linked below.
https://arxiv.org/pdf/...9
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