TouchLogger: inferring keystrokes on touch screen from smartphone motion 论文

摘要

Attacks that use side channels, such as sound and electromagnetic emanation, to infer keystrokes on physical keyboards are ineffective on smartphones without physical keyboards. We describe a new side channel, motion, on touch screen smartphones with only soft keyboards. Since typing on different locations on the screen causes different vibrations, motion data can be used to infer the keys being typed. To demonstrate this attack, we developed TouchLogger, an Android application that extracts features from device orientation data to infer keystrokes. TouchLogger correctly inferred more than 70 % of the keys typed on a number-only soft keyboard on a smartphone. We hope to raise the awareness of motion as a significant side channel that may leak confidential data. 1