Accepted author manuscript, 2.95 MB, PDF document
Available under license: CC BY: Creative Commons Attribution 4.0 International License
Final published version
Licence: CC BY: Creative Commons Attribution 4.0 International License
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Defeat Your Enemy Hiding Behind Public WiFi
T2 - WiGuard Can Protect Your Sensitive information from CSI-based Attack
AU - Zhang, Jie
AU - Tang, Zhanyong
AU - Li, Meng
AU - Chen, Xiaojiang
AU - Fang, Dingyi
AU - Wang, Zheng
PY - 2018/3/28
Y1 - 2018/3/28
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 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 input information in a public place. Our approach carefully exploits WiFi channel interference to introduce noise to attacker’s CSI measurements to reduce the success rate of CSI-based attacks. 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-based attacks from 92–42% for text-based passwords and from 82–22% 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 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 input information in a public place. Our approach carefully exploits WiFi channel interference to introduce noise to attacker’s CSI measurements to reduce the success rate of CSI-based attacks. 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-based attacks from 92–42% for text-based passwords and from 82–22% for pattern lock.
KW - CSI-based attack
KW - channel interference
KW - sensitive information protection
U2 - 10.3390/app8040515
DO - 10.3390/app8040515
M3 - Journal article
VL - 8
JO - Applied Sciences
JF - Applied Sciences
SN - 2076-3417
IS - 4
M1 - 515
ER -