Location-based services (LBS) which bring so much convenience to our daily life have been intensively studied over the years. Generally, an LBS query processing can be categorized into snapshot and continuous queries which access user location information and return search results to the users. An LBS has full control of the location information, causing user privacy concerns. If an LBS provider has a malicious intention to breach the user privacy by tracking the users' routes to their destinations, it incurs a serious threat. Most existing techniques have addressed privacy protection mainly for snapshot queries. However, providing privacy protection for continuous queries is of importance, since a malicious LBS can easily obtain complete user privacy information by observing a sequence of successive query requests. In this paper, we propose a comprehensive trajectory privacy technique and combine ambient conditions to cloak location information based on the user privacy profile to avoid a malicious LBS reconstructing a user trajectory. We first propose an r-anonymity mechanism which preprocesses a set of similar trajectories R to blur the actual trajectory of a service user. We then combine k-anonymity with s road segments to protect the user's privacy. We introduce a novel time-obfuscated technique which breaks the sequence of the query issuing time for a service user to confuse the LBS so it does not know the user trajectory, by sending a query randomly from a set of locations residing at the different trajectories in R. Despite the randomness incurred from the obfuscation process for providing strong trajectory privacy protection, the experimental results show that our trajectory privacy technique maintains the correctness of the query results at a competitive computational cost.

Owing to the wide availability of the global positioning system (GPS) and digital mapping of roads, road network navigation services have become a basic application on many mobile devices. Path planning, a fundamental function of road network navigation services, finds a route between the specified start location and destination. The efficiency of this path planning function is critical for mobile users on roads due to various dynamic scenarios, such as a sudden change in driving direction, unexpected traffic conditions, lost or unstable GPS signals, and so on. In these scenarios, the path planning service needs to be delivered in a timely fashion. In this paper, we propose a system, namely, Path Planning by Caching (PPC), to answer a new path planning query in real time by efficiently caching and reusing historical queried-paths. Unlike the conventional cache-based path planning systems, where a queried-path in cache is used only when it matches perfectly with the new query, PPC leverages the partially matched queries to answer part(s) of the new query. As a result, the server only needs to compute the unmatched path segments, thus significantly reducing the overall system workload. Comprehensive experimentation on a real road network database shows that our system outperforms the state-of-the-art path planning techniques by reducing 32 percent of the computation latency on average.