A Compact, Wireless, Wearable Sensor Network for Interactive Dance Ensembles
BSN '06 Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks
Timing analysis of keystrokes and timing attacks on SSH
SSYM'01 Proceedings of the 10th conference on USENIX Security Symposium - Volume 10
Stealthy video capturer: a new video-based spyware in 3G smartphones
Proceedings of the second ACM conference on Wireless network security
Gesture Recognition with a 3-D Accelerometer
UIC '09 Proceedings of the 6th International Conference on Ubiquitous Intelligence and Computing
Defending against sensor-sniffing attacks on mobile phones
Proceedings of the 1st ACM workshop on Networking, systems, and applications for mobile handhelds
Keyboard acoustic emanations revisited
ACM Transactions on Information and System Security (TISSEC)
uWave: Accelerometer-based personalized gesture recognition and its applications
Pervasive and Mobile Computing
Shake well before use: authentication based on accelerometer data
PERVASIVE'07 Proceedings of the 5th international conference on Pervasive computing
GesturePIN: using discrete gestures for associating mobile devices
Proceedings of the 12th international conference on Human computer interaction with mobile devices and services
Compromising electromagnetic emanations of wired and wireless keyboards
SSYM'09 Proceedings of the 18th conference on USENIX security symposium
Timing attacks on PIN input devices
Proceedings of the 17th ACM conference on Computer and communications security
A dynamic time warping approach to real-time activity recognition for food preparation
AmI'10 Proceedings of the First international joint conference on Ambient intelligence
Online gesture recognition for user interface on accelerometer built-in mobile phones
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: models and applications - Volume Part II
TouchLogger: inferring keystrokes on touch screen from smartphone motion
HotSec'11 Proceedings of the 6th USENIX conference on Hot topics in security
ACCessory: password inference using accelerometers on smartphones
Proceedings of the Twelfth Workshop on Mobile Computing Systems & Applications
Practicality of accelerometer side channels on smartphones
Proceedings of the 28th Annual Computer Security Applications Conference
Identity, location, disease and more: inferring your secrets from android public resources
Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security
Seeing double: reconstructing obscured typed input from repeated compromising reflections
Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security
PIN skimmer: inferring PINs through the camera and microphone
Proceedings of the Third ACM workshop on Security and privacy in smartphones & mobile devices
Hi-index | 0.00 |
Recent researches have shown that motion sensors may be used as a side channel to infer keystrokes on the touchscreen of smartphones. However, the practicality of this attack is unclear. For example, does this attack work on different devices, screen dimensions, keyboard layouts, or keyboard types? Does this attack depend on specific users or is it user independent? To answer these questions, we conducted a user study where 21 participants typed a total of 47,814 keystrokes on four different mobile devices in six settings. Our results show that this attack remains effective even though the accuracy is affected by user habits, device dimension, screen orientation, and keyboard layout. On a number-only keyboard, after the attacker tries 81 4-digit PINs, the probability that she has guessed the correct PIN is 65%, which improves the accuracy rate of random guessing by 81 times. Our study also indicates that inference based on the gyroscope is more accurate than that based on the accelerometer. We evaluated two classification techniques in our prototype and found that they are similarly effective.