Malboard: A novel user keystroke impersonation attack and trusted detection framework based on side-channel analysis
Published in Computers & Security, 2019
Overview
Keystroke dynamics are often used as a behavioral biometric to verify users based on typing rhythms. This paper examines an attack using a modified USB keyboard that learns a user’s typing patterns to bypass biometric verification. We also present a detection framework that uses acoustic emissions and USB communication timing to distinguish authentic user keystrokes from automated hardware injections.
Recommended citation: Nitzan Farhi, Nir Nissim, Yuval Elovici, "Malboard: A novel user keystroke impersonation attack and trusted detection framework based on side-channel analysis." Computers & Security, Vol. 85, pp. 240-269, 2019.
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