Liang Cai and Hao Chen UC Davis Security Problems on Smartphones Old problems Malware Software bugs Information leak New problems How can attackers exploit sensors Sensors on ID: 778162
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Slide1
TouchLogger: Inferring Keystrokes on Touch Screen from Smartphone Motion
Liang
Cai
and
Hao
Chen
UC Davis
Slide2Security Problems on SmartphonesOld problemsMalwareSoftware bugsInformation leak
…
New problems
How can attackers exploit sensors?
Slide3Sensors on SmartphonesPrivacy-sensitive sensorsMicrophonesCamerasGPS
Are motion sensors privacy-sensitive?
Accelerometers
Gyroscopes
Slide4Traditional KeyloggersIntercepting key eventsE.g., Trojan programsUsing out of channelsAcoustic frequency signatures of keys
Timing between keystrokes
Electromagnetic emanations of keystrokes
Work well on physical keyboards
But not on software keyboards
Slide5Keylogger for Soft KeyboardNew out of band channel on smartphonesAccelerometers
Gyroscopes
Insight: motion sensor data can infer keystrokes
Slide6Threat ModelKeylogger can read motion sensorMost users do NOT regard motion sensors as sensitive data sourceW3C’s DeviceOrientation
Event Specification allows web applications to read motion sensors via JavaScript
supported by both Android 3.0 and
iOS
4.2
User does NOT place phone on fixed surface
Slide7Modeling Typing-Induced MotionShift is affected byStriking force of the typing fingerResistance force of the supporting handRotation is affected by
Landing location of the typing finger
Location of the supporting hand on the phone
We observe
Shift is more likely user dependent
Rotation is more likely user independent
Slide8Device OrientationDevice orientation event consists ofα: Device rotates along z-axis (perpendicular to the screen plane)β: Device rotates along x-axis (parallel to the shorter side of screen)
γ
: Device rotates along y-axis (parallel to the longer side of screen)
We use only
β
and
γ
Slide9Feature Extraction
Slide10Feature Extraction
Slide11EvaluationHTC Evo 4G smartphoneDigits 0 … 9 on number-only soft keyboard
Slide12ResultsCollected 3 datasets2 smaller datasets for trainingThe largest dataset (449 keystrokes) for testingCorrectly inferred 321 out of 449 (71.5%) keystrokes.
Slide13Detailed Inference Results
Slide14Training Set Size
Slide15ConclusionMotion sensors on smart phones may reveal keystrokesNeed to protect motion sensors as diligently as other sensors