| Summary: | The worldwide deployment of mobile devices incorporated into our everyday activities made available an abundance of private location information. This information has sparked many innovative applications, but raised challenging users’ location-privacy problems. This thesis is concerned with the problem of offering source fc-anonymity location-privacy when contacting a Location-based Service (LBS) using Opportunistic Networks (OppNets). We propose a novel, fully distributed, self organized and collaborative fc-anonymity protocol (Location-Privacy-Aware Forwarding (LPAF) protocol) to protect users’ location information and offer better privacy while communicating with an untrusted LBS over OppNet. LPAF enables users to collaborate in building a social-based untraceable obfuscation path to communicate with the LBS. We utilize a lightweight multi-hop Markov-based stochastic model for location prediction to guide queries towards the LBS’s location as well as to reduce required resources in terms of re-transmission overheads. We develop a formal analytical model and present theoretical analysis and simulation of the proposed protocol performance. We perform extensive simulation over pseudo-realistic city-map using map-based mobility models, and using real-world data traces to compare LPAF to existing state-of-the-art and benchmark location-privacy protocols. We show that LPAF manages to perform better across three performance dimensions (he. quality of service -success ratio-, quality of anonymization -number of obfuscation hops- and energy efficiency -obfuscation re-transmission overhead-). LPAF achieves higher privacy levels and better success ratio and delay compared to other protocols while maintaining lower overheads. Simulation results show that LPAF outperforms other distributed protocols in terms of success ratio for pseudo realistic scenarios. We have conducted a more realistic evaluation over OppNets using two real-world data traces. Results show that LPAF can offer better location-privacy and higher success ratio compared to other protocols in scenarios with moderate social network size, but with a slight increase in delay.
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