Robust Wi-Fi fingerprinting-based positioning in the presence of lying identities

2018 International Joint Conference on Materials Science and Mechanical Engineering

Lu, Wei-Chung^1 ; Yeh, Shih-Chun^1 ; Chuang, Chung-Chih^1 ; Fang, Shih-Hau^1

Yuan Ze University, Taiwan^1

关键词: Access points;    Bayesian approaches;    Cluster-based methods;    Robust location estimation;    Wi-Fi fingerprinting;    Wi-Fi localizations;    Wi-Fi Positioning;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/383/1/012054/pdf
DOI  :  10.1088/1757-899X/383/1/012054

来源: IOP

【 摘 要 】

The lying identity of an access point (AP) is one of the most serious threat in Wi-Fi positioning because an adversary can easily acquire a valid address by monitoring the transmission and masquerade as another AP in the networks. This study proposes a robust Wi-Fi localization algorithm that can tolerate the liars instead of explicitly detecting them. The proposed algorithm considers all possible combinations of APs in an unionbased approach such that the adversaries cannot easily affect the positioning results by masquerading APs. Onsite experimental results demonstrate that this approach apparently achieves more robust location estimation than the Bayesian approach and the cluster-based method in the presence of lying identities.