Privacy preserving in indoor fingerprint localization and radio map expansion

People spend most of their life time in indoor environments and in all of these environments, Location Service Providers (LSPs) improve users' navigation. Preserving privacy in Location Based Services (LBSs) is vital for indoor LBSs and fingerprinting based indoor localization method is an emerging technique in indoor localization. In such systems, LSP may be curious and untrusted. Therefore, it is preferred that user estimates its location by using a Partial Radio Map (PRM) which is achieved by LSP, anonymously. In this paper, a privacy preserving method that uses Bloom filter for preserving anonymity and creating PRM during localization process, is proposed. In this method, LSP cannot recognize user identity, which is anonymized by the anonymizer. The proposed method has lower computational complexity compared with methods that use encryption or clustering concepts. The proposed method also has higher accuracy in localization compared with those that use Bloom filter with one random selected AP. Then, in order to decrease the complexity and to increase the accuracy at the same time, we introduce a method that expands the radio map by authenticated users, without compromising their privacy. We also enhance the performance of this method, using Hilbert curve for preserving the ambiguity of users' location. After verifying the user's data, LSP sends a certificate to the authenticated users. This certificate can increase the priority of users in LBS requests. Simulation results and measurements show that the proposed method on average improves the localization accuracy up to 16% compared with existing location privacy methods.