Journal Article10.1002/SEC.323
Toward attack-resistant localization under infrastructure attacks
Jie Yang,Yingying Chen +1 more
TL;DR: The application of the attack-resistant 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.
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Abstract: 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.
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Citations
Protecting multi-lateral localization privacy in pervasive environments
Tao Shu,Yingying Chen,Jie Yang +2 more
TL;DR: This paper forms the problem as a secure least-squared-error (LSE) estimation for an overdetermined linear system and develops three privacy-preserving solutions by leveraging combinations of information-hiding and homomorphic encryption, which provide different levels of protection for location-side information and resilience to node collusion.
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•Journal Article
Robustness of localization accuracy for wireless sensor networks under physical attacks
TL;DR: A solution based on multi frequency multi power antenna to provide robust and accurate localization technique and a grid coloring algorithm to detect the signal hole map in the network which is refer to the attack prone regions in order to take a corrective actions are proposed.
2
Multi-lateral Privacy-Preserving Localization in Pervasive Environments
Tao Shu,Yingying Chen,Jie Yang,Albert Williams +3 more
- 08 Jul 2014
TL;DR: Three privacy-preserving localization solutions are developed by leveraging combinations of information hiding and homomorphic encryption, which provide different levels of protection for location side information and resilience to node collusion, and have the advantage of being able to trade user's privacy requirements for better computation/communication efficiency.
A Survey on Secure Range Based Localization Algorithms in Wireless Sensor Networks
Ahmed Abdulqader,Hussein AL-Qaysi,Tharek A. Rahman +2 more
- 01 Jan 2014
TL;DR: This paper analyzes the attacks on the Range Based methods and surveys the current work on attack detection and resolution in localization.
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