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Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Protect sensitive information against channel state information based attacks
AU - Zhang, Jie
AU - Tang, Zhanyong
AU - Chen, Xiaojiang
AU - Fang, Dingyi
AU - Li, Rong
AU - Wang, Zheng
N1 - ©2017 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
PY - 2017/8/18
Y1 - 2017/8/18
N2 - Channel state information (CSI) has been recently shown to be useful in performing security attacks in public WiFi environments. By analyzing how CSI is affected by the finger motions, CSI-based attacks can effectively reconstruct text-based passwords and locking patterns. This paper presents WiGuard, a novel system to protect sensitive on-screen gestures in a public place. Our approach carefully exploits the WiFi channel interference to introduce noise into the attacker's CSI measurement to reduce the success rate of the attack. Our approach automatically detects when a CSI-based attack happens. We evaluate our approach by applying it to protect text-based passwords and pattern locks on mobile devices. Experimental results show that our approach is able to reduce the success rate of CSI attacks from 92% to 42% for text-based passwords and from 82% to 22% for pattern lock.
AB - Channel state information (CSI) has been recently shown to be useful in performing security attacks in public WiFi environments. By analyzing how CSI is affected by the finger motions, CSI-based attacks can effectively reconstruct text-based passwords and locking patterns. This paper presents WiGuard, a novel system to protect sensitive on-screen gestures in a public place. Our approach carefully exploits the WiFi channel interference to introduce noise into the attacker's CSI measurement to reduce the success rate of the attack. Our approach automatically detects when a CSI-based attack happens. We evaluate our approach by applying it to protect text-based passwords and pattern locks on mobile devices. Experimental results show that our approach is able to reduce the success rate of CSI attacks from 92% to 42% for text-based passwords and from 82% to 22% for pattern lock.
U2 - 10.1109/CSE-EUC.2017.221
DO - 10.1109/CSE-EUC.2017.221
M3 - Conference contribution/Paper
SN - 9781538632208
BT - 2017 IEEE International Conference on Computational Science and Engineering (CSE) and Embedded and Ubiquitous Computing (EUC)
PB - IEEE
T2 - The 2017 IEEE International Conference on Smart X
Y2 - 21 July 2017 through 23 July 2017
ER -