TY - GEN
T1 - MultiAuth
T2 - 22nd International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, MobiHoc 2021
AU - Kong, Hao
AU - Lu, Li
AU - Yu, Jiadi
AU - Chen, Yingying
AU - Xu, Xiangyu
AU - Tang, Feilong
AU - Chen, Yi Chao
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/7/26
Y1 - 2021/7/26
N2 - With the increasing integration of humans and the cyber world, user authentication becomes critical to support various emerging application scenarios requiring security guarantees. Existing works utilize Channel State Information (CSI) of WiFi signals to capture single human activities for non-intrusive and device-free user authentication, but multi-user authentication remains a challenging task. In this paper, we present a multi-user authentication system, MultiAuth, which can authenticate multiple users with a single commodity WiFi device. The key idea is to profile multipath components of WiFi signals induced by multiple users, and construct individual CSI from the multipath components to solely characterize each user for user authentication. Specifically, we propose a MUltipath Time-of-Arrival measurement algorithm (MUTA) to profile multipath components of WiFi signals in high resolution. Then, after aggregating and separating the multipath components related to users, MultiAuth constructs individual CSI based on the multipath components to solely characterize each user. To identify users, MultiAuth further extracts user behavior profiles based on the individual CSI of each user through time-frequency analysis, and leverages a dual-task neural network for robust user authentication. Extensive experiments involving 3 simultaneously present users demonstrate that MultiAuth is accurate and reliable for multi-user authentication with 87.6% average accuracy and 8.8% average false accept rate.
AB - With the increasing integration of humans and the cyber world, user authentication becomes critical to support various emerging application scenarios requiring security guarantees. Existing works utilize Channel State Information (CSI) of WiFi signals to capture single human activities for non-intrusive and device-free user authentication, but multi-user authentication remains a challenging task. In this paper, we present a multi-user authentication system, MultiAuth, which can authenticate multiple users with a single commodity WiFi device. The key idea is to profile multipath components of WiFi signals induced by multiple users, and construct individual CSI from the multipath components to solely characterize each user for user authentication. Specifically, we propose a MUltipath Time-of-Arrival measurement algorithm (MUTA) to profile multipath components of WiFi signals in high resolution. Then, after aggregating and separating the multipath components related to users, MultiAuth constructs individual CSI based on the multipath components to solely characterize each user. To identify users, MultiAuth further extracts user behavior profiles based on the individual CSI of each user through time-frequency analysis, and leverages a dual-task neural network for robust user authentication. Extensive experiments involving 3 simultaneously present users demonstrate that MultiAuth is accurate and reliable for multi-user authentication with 87.6% average accuracy and 8.8% average false accept rate.
KW - Individual CSI construction
KW - Multi-user authentication
KW - Multipath profiling
KW - WiFi signals
UR - https://www.scopus.com/pages/publications/85121602156
U2 - 10.1145/3466772.3467032
DO - 10.1145/3466772.3467032
M3 - 会议稿件
AN - SCOPUS:85121602156
T3 - Proceedings of the International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc)
SP - 31
EP - 40
BT - MobiHoc 2021 - Proceedings of the 2021 22nd International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing
PB - Association for Computing Machinery
Y2 - 26 July 2021 through 29 July 2021
ER -