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Recognizing Keystrokes Using WiFi Devices

delete2017-05-01
delete90
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OA
AI
K
Kamran Ali
A
Alex X. Liu *
W
Wei Wang
M
Muhammad Shahzad
DOI:10.1109/JSAC.2017.2680998delete
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Abstract

Abstract

En 中文
Keystroke privacy is critical for ensuring the security of computer systems and the privacy of human users as what is being typed could be passwords or privacy sensitive information. In this paper, we show for the first time that WiFi signals can also be exploited to recognize keystrokes. The intuition is that while typing a certain key, the hands and fingers of a user move in a unique formation and direction and thus generate a unique pattern in the time-series of channel state information (CSI) values, which we call CSI-waveform for that key. In this paper, we propose a WiFi signal-based keystroke recognition system called WiKey. WiKey consists of two commercial off-the-shelf WiFi devices, a sender (such as a router) and a receiver (such as a laptop). The sender continuously emits signals and the receiver continuously receives signals. When a human subject types on a keyboard, WiKey recognizes the typed keys based on how the CSI values at the WiFi signal receiver end. We implemented the WiKey system using a TP-Link TL-WR1043ND WiFi router and a Lenovo X200 laptop. WiKey achieves over 97.5% detection rate for detecting the keystroke and 96.4% recognition accuracy for classifying single keys. In real-world experiments, WiKey can recognize keystrokes in a continuously typed sentence with an accuracy of 93.5%. WiKey can also recognize complete words inside a sentence with over 85% accuracy.
Keywords:
Keystroke recognition
wireless sensing
human computer interaction (HCI)
wireless security
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Journal

IEEE Journal on Selected Areas in Communications cover
IEEE Journal on Selected Areas in Communications
IF:
17.2
Papers:
6.4K
Citations:
3.1W

Organization

N
nanjing university
Scholars:
7.8W
Papers: 5.6W
Citations: 87
M
michigan state university
Scholars:
3.6W
Papers: 3.2W
Citations: 44
N
North Carolina State University
Scholars:
2.6W
Papers: 2.3W
Citations: 3.7W
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