Your WiFi Can See You – Bombthrower 9/18/23


When police suspected Danny Kyllo, an Oregon man, of growing cannabis in his home they drove to his house with a thermal imaging device to scan it. They found hot pockets in the house, which were used to obtain a search warrant and subsequently bust Kyllo.

Fortunately, a 5-4 Supreme Court decision ruled the scan an unlawful search under the Fourth Amendment, requiring a warrant the police did not obtain. Score one for privacy, but the government is about to have a far more controversial and dangerous tool at its disposal to monitor what’s going on inside your home.

Unlike a thermal imager, this device is already in your home – and you put it there.

WiFi is electromagnetic waves in the 2.4 and 5 GHz ranges. It’s the same thing as the light you see, only it can penetrate walls due to its much longer wavelength. Just like light (and echolocation) these waves also reflect off various surfaces and, when reconstructed properly, can be used to create an image.

Development of this technology goes back at least as far as July 2005, where researchers claimed at an IEEE Symposium that they had created an ultra-wideband high-resolution short pulse imaging radar system operating around 10 GHz. The applications for which were explicitly for military and police use, providing them with “enhanced situation awareness.”

A few years later, in 2008, researchers at UC Santa Barbara created an initial approach for imaging with WiFi that they presented at IEEE ACC 2009. A year later they demonstrated the feasibility of this approach.

Sensing the potential of this new surveillance technology, other researchers began piling on. Progress was initially slow but, in 2017, two researchers in Germany demonstrated the ability to do WiFi imaging using techniques borrowed from the field of holography. According to Philipp Holl, an undergrad student and lead study author who worked with Friedemann Reinhard of the Technical University of Munich to develop the new method, “The past two years have seen an explosion of methods for passive Wi-Fi imaging.”

At the time, the technology could only make out rough shapes of things. “If there’s a cup of coffee on a table, you may see something is there, but you couldn’t see the shape,” Holl says, “but you could make out the shape of a person, or a dog on a couch. Really any object that’s more than 4 centimeters in size.”

In 2018 the team at UC Santa Barbara published a paper titled “Et Tu Alexa?” examining the potential threats of this emerging technology. They examined the problem of adversarial WiFi sensing and the risk to privacy resulting from the widespread deployment of wireless devices, which could be used to track your precise physical location, movement, and other physiological properties.

Fortunately, they also propose some countermeasures for defending against such attacks to reduce the quantity and quality of the WiFi signals captured by the attacker, such as Geo-fencing and rate-limiting. These methods are not as effective with IoT devices, though, due to the frequency with which they make transmissions.

Up until this point it was necessary to use frequencies higher than commercial WiFi (2.4 and 5 GHz) to achieve decent imaging resolutions. That all changed in February 2019 when a team from Michigan State University published a paper in IEEE Access outlining how they were able to use signals at 5.5 GHz, which matches the 802.11n/ac WiFi protocol, to create a 2-D image of two reflecting spheres and a reflecting X-shaped target, concluding “full 2-D imagery is possible by capturing the WiFi signals present in typical environments.”

At MobiCom 2020, researchers from the University of Buffalo, presented their WiPose technology, touted as “the first 3-D human pose construction framework using commercial WiFi devices.” This system uses the 2-D imaging technology previously discussed to construct a 3-D avatar of the humans captured by it. The system uses a deep learning model that encodes the prior knowledge of human skeletons in the construction process of the 3-D model….

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