The active badge location system
ACM Transactions on Information Systems (TOIS)
The Cricket location-support system
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
A Statistical Modeling Approach to Location Estimation
IEEE Transactions on Mobile Computing
Localization from mere connectivity
Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing
WLAN Location Determination via Clustering and Probability Distributions
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
Range-free localization schemes for large scale sensor networks
Proceedings of the 9th annual international conference on Mobile computing and networking
Secure verification of location claims
WiSe '03 Proceedings of the 2nd ACM workshop on Wireless security
Distributed localization in wireless sensor networks: a quantitative comparison
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Wireless sensor networks
Wireless Communications
Robust statistical methods for securing wireless localization in sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Attack-resistant location estimation in sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
A security and robustness performance analysis of localization algorithms to signal strength attacks
ACM Transactions on Sensor Networks (TOSN)
Indoor localization using improved RSS-based lateration methods
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
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Trustworthy location information is important because it is a critical input to a wide variety of location-based applications. However, the localization infrastructure is vulnerable to physical attacks, and consequently, the localization results are affected. In this paper, we aim to achieve robust localization under infrastructure attacks. We first investigated the impact of infrastructure attacks on localization and showed that the performance of location estimations degraded significantly under the attack. We then derived an attack-resistant scheme that is not algorithm specific and can be integrated with existing localization algorithms. Our attack-resistant scheme exploited the characteristics of the geometric patterns returned by location estimates under the attack; that is, the localization results of a wireless device under the normal situation were clearly clustered together, whereas the localization results were scattered when an attack was present. Thus, our attack-resistant scheme is grounded on K-means clustering analysis of intra-distance of localization results from all possible combinations of any three access points. To evaluate the effectiveness and scalability of our proposed scheme, we used received signal strength for validation and applied our approach to three broad classes of localization algorithms: lateration based, fingerprint matching, and Bayesian networks. We validated our scheme in the ORBIT test bed (North Brunswick, NJ, USA) using an 802.11 (Wi-Fi) network and in a real office building environment using an 802.15.4 (ZigBee) network. The extensive experimental results demonstrated that the application of our scheme could help the broad range of localization algorithms to achieve comparable or even better localization performance when under infrastructure attacks as compared with normal situations without attack, thus, effectively eliminating the effects of infrastructure attacks. Copyright © 2011 John Wiley & Sons, Ltd.