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Silence is Golden: Enhancing Privacy of Location-Based Services by Content Broadcasting and Active Caching in Wireless Vehicular Networks

The privacy issue of location-based service (LBS) applications represents a fundamental and critical research topic that shows distinguished challenges. Specifically, in the scenario of vehicular networks, due to connectivity transitory and throughput degradation caused by high vehicle mobility, traditional methods such as k-anonymity are not sufficient. In an effort to address this issue, we propose a framework that enhances the privacy of LBS by actively caching in the wireless vehicular network scenario. The scheme is designed under the dedicated short-range communication (DSRC) standard, with three original contributions. First, a point-of-interest (POI) query probability model for in-vehicle users is defined, considering the spatial relationship between the current location and the queried location. Second, three broadcasting content selection algorithms of the roadside unit (RSU) are proposed, including two adaptive updating methods and one knowledge-based precaching (KBPC) method. Third, we identify critical parameters that affect privacy, including RSU distance, vehicle speed, query set size of POI, size of each POI entry, and the proportion of channel capacity used for RSU broadcast (defined as channel occupancy). Finally, the proposed scheme is evaluated by extensive simulations, and the results are discussed in detail.