Researchers have tested a technique to detect the vibrations of a mobile phone''s earpiece and decipher what the person on the other side of the call was saying with up to 883 percent accuracy. The researchers at Pennsylvania State University used an off-the-shelf automotive radar sensor and a novel processing technique to dispel this significant security danger.
"As technology becomes more reliable and robust over time, adversaries may be able to misuse such sensing techniques," said Penn State''s Suryoday Basak.
"Our demonstration of this type of exploitation contributes to the scientific literature that broadly states, "Hey! Automotive radars can be used to intercept audio," Basak said.
The radar is used in the millimetre-wave (mmWave) spectrum, specifically in the bands of 60 to 64GHz and 77 to 81GHz, which enabled the researchers to define their technique "mmSpy." This is a subset of the radio spectrum used for 5G, the fifth-generation standard for communication systems around the globe.
Researchers used a mmSpy simulation simulated people talking through the earpiece of a smartphone in the 2022 IEEE Symposium on Security and Privacy.
The speaker of the phone vibrates from the speech, and this vibration spreads throughout the phone''s body.
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"We use the radar to sense this vibration and reconstruct what happened to the person on the other side of the line," says Basak.
Mahanth Gowda, an assistant professor at Penn State, said that their approach works even if the sound is completely unaudible to both humans and microphones nearby.
"This isn''t the first time similar vulnerabilities or attack methods have been discovered, but this particular feature of hearing and reconstructing speech from the other side of a smartphone line was not yet explored, according to Basak.
The researchers then provide a machine learning package that is being taught to classify speech and reconstruct audio.
The processed speech, which is higher than expected by the radar, is 88% accuracy when it comes to phones. According to officials, the radar has reduced to 43 percent accuracy at six feet when it detects vibrations from a foot away.
According to Basak, researchers may then filter, enhance, or classify words once the speech is restored.
The company is continuing to refine their approach so that people may better understand non only how to protect against this security danger, but also how to exploit it for the benefit.
"The methodology that we developed can also be used to detect vibrations in industrial machinery, smart home systems, and building-monitoring systems," Basak said.
According to the authors, there are similar home maintenance or even health monitoring systems that might benefit from such sensitive tracking.
"Imagine a radar that might track a user and request help if some health parameter changes in a dangerous way," Basak said.
"With the correct set of target actions, radars in smart homes and industries may enable a rapid turnaround when issues and issues are identified, according to a researcher.