A team of researchers has developed a new attack eavesdrop UP Android devicesThis advanced device allows you to identify the gender and identity of the caller and even distinguish speech.
And call EarSpy developerThe side channel attachment aims to explore new eavesdropping capabilities by receiving motion sensor data recordings generated by earphone feedback in mobile devices.
As for the side channel attack, cyber attacks exploit target vulnerabilities, whether at the level of operating systems, applications, networks, algorithms, cryptography, protocols or other components and settings that are in use in that target, but side channel attacks do not depend on the existence of a security hole It is directed in the target, but they do depend on the exploitation of some of the information that can be collected on the system during its operation.
And promise EarSpy An academic effort by researchers from five US universities: Texas A&M University, New Jersey Institute of Technology, Temple University, University of Dayton, and Rutgers University University).
This type of attack has previously been seen in smartphone speakers, but they are still too weak to generate enough vibration to put users at risk of eavesdropping.
The latest smartphones also use more powerful stereo speakers than the models released a few years ago and are capable of much better sound quality and stronger vibrations.
Newer devices also use more sensitive motion and gyroscope sensors that can record even the smallest level of resonance from speakers.
In their experiments, the researchers used two phones, one of which was launched in 2016 – OnePlus 3T, and the other was launched in 2019 – OnePlus 7T. And the difference between them was obvious.
Using readily available datasets, the researchers trained a machine learning (ML) algorithm to identify voice content and caller identity and gender. Test data varied by data set and device, but generally yielded promising results for eavesdropping.
Caller gender identification on the OnePlus 7T ranged from 77.7% to 98.7%, speaker identification from 63.0% to 91.2%, and voice recognition from 51.8% to 56.4 %.
As for the OnePlus 9, the rate for gender identification increased to 88.7% and speaker identification fell to 73.6% on average, while the rate for speech recognition ranged between 33 .3% and 41.6%.
It is reported that using the speakerphone and the Spearphone app, the researchers developed a similar attack during their experiments in 2020, and the accuracy of identifying the caller’s gender and knowing it reached 99%, while the accuracy speech recognition has reached 80%. .
The researchers recommend that phone manufacturers ensure that sound pressure is kept constant during calls and place motion sensors in a place where internally generated vibrations have no, or at least minimal, effect.
