Simple defences against vibration-based keystroke fingerprinting attacks

Smartphones are increasingly equipped with sensitive accelerometers that can analyse acoustic vibrations on a physical surface. This allows them to gain a covert understanding of the surrounding environment by combining accelerometer sampling with sophisticated signal processing techniques. In this work, we analyse keyboard-sniffing attacks based on acoustic (vibration) covert channels, launched from a malicious application installed on a smartphone. An important requirement of such attacks is access to reliable acoustic signals that can be distinguished from the noise floor by applying appropriate signal processing techniques. Our analysis indicates that state-of-the-art attack techniques are fragile; injecting randomised noise (jamming) via the vibration medium into the accelerometer, reduces the efficiency of the attack from 80% to random guessing. We conclude that our work presents an important step towards disabling the covert channel and ensuring full security.