Poster: Exploiting Keystroke Dynamics via mmWave Radar for Application Profiling
C. J. Kang, Dongjin Seo, Sihun Yang, Jun Young Han · 2024
Even seemingly innocuous computer usage information often leads to targeted privacy attacks. In this poster, we present mmProfiler, a novel privacy attack that aims to remotely infer user's running application. mmProfiler leverages mmWave radar-based vibrometry to capture minute vibration induced by the victim's keystrokes. Captured data is then analyzed to extract keystroke patterns, or keystroke dynamics, used to profile the running application the user is engaged with. Our preliminary experiment demonstrates the potential of mmProfiler, with 84% accuracy in discerning between five user applications.