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      As per Latest Research Mobile Phone Calls Eavesdropped Remotely Using Sensors | Details Inside

      Researchers have demonstrate a method 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 83% accuracy. The team at Pennsylvania State University use an off-the-shelf automotive radar sensor and a novel processing approach to reveal this significant security concern.

      Suryoday Basak, a doctoral candidate at Penn State Said :

      “As technology becomes more reliable and robust over time, the misuse of such sensing technologies by adversaries becomes probable,”.

      “Our demonstration of this kind of exploitation contributes to the pool of scientific literature that broadly says, ‘Hey! Automotive radars can be used to eavesdrop audio. We need to do something about this,”.

      The radar operates in the millimetre-wave (mmWave) spectrum, specifically in the bands of 60 to 64GHz and 77 to 81GHz, which inspire the researchers to name their approach “mmSpy.”

      This is a subset of the radio spectrum use for 5G, the fifth-generation standard for communication systems across the globe.

      In the mmSpy demonstration, describe in the 2022 IEEE Symposium on Security and Privacy (SP), the researchers simulate people speaking through the earpiece of a smartphone.

      The phone’s earpiece vibrates from the speech, and that vibration permeates across the body of the phone.

      “We use the radar to sense this vibration and reconstruct what was said by the person on the other side of the line,” said Basak.

      The researchers, including Mahanth Gowda, an assistant professor at Penn State, noted that their approach works even when the audio is completely inaudible to both humans and microphones nearby.

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      Suryoday Basak Said :

      “This isn’t the first time similar vulnerabilities or attack modalities have been found, but this particular aspect — detecting and reconstructing speech from the other side of a smartphone line — was not yet explored,”.

      The radar sensor data is pre-process via MATLAB and Python modules, which are computing platform-language interfaces used to remove hardware-related and artefact noise from the data.

      The researchers then feed that to machine learning modules trained to classify speech and reconstruct audio.

      When the radar senses vibrations from a foot away, the process speech is 83% accuracy.

      That drops the farther the radar moves from the phone, down to 43% accuracy at six feet, they said.

      Once the speech is reconstruct, the researchers can then filter, enhance or classify keywords as needed, Suryoday Basak said.

      The team is continuing to refine their approach to better understand not only how to protect against this security vulnerability, but also how to exploit it for good.

      Suryoday Basak Said :

      “The methodology that we developed can also be used for sensing vibrations in industrial machinery, smart home systems and building-monitoring systems,”.

      According to the researchers, there are similar home maintenance or even health monitoring systems that could benefit from such sensitive tracking.

      Suryoday Basak Said :

      “Imagine a radar that could track a user and call for help if some health parameter changes in a dangerous way,”.

      “With the right set of target actions, radars in smart homes and industry can enable a faster turnaround when problems and issues are detected,”.

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