%AShahid, Abdur%APissinou, Niki%AIyengar, S.S.%AMiller, Jerry%ADing, Ziqian%ALemus, Teresita%D2018%I %K %MOSTI ID: 10135144 %PMedium: X %TKLAP for Real-World Protection of Location Privacy %XIn Location-Based Services (LBS), users are required to disclose their precise location information to query a service provider. An untrusted service provider can abuse those queries to infer sensitive information on a user through spatio-temporal and historical data analyses. Depicting the drawbacks of existing privacy-preserving approaches in LBS, we propose a user-centric obfuscation approach, called KLAP, based on the three fundamental obfuscation requirements: k number of locations, l-diversity, and privacy area preservation. Considering user's sensitivity to different locations and utilizing Real-Time Traffic Information (RTTI), KLAP generates a convex Concealing Region (CR) to hide user's location such that the locations, forming the CR, resemble similar sensitivity and are resilient against a wide range of inferences in spatio-temporal domain. For the first time, a novel CR pruning technique is proposed to significantly improve the delay between successive CR submissions. We carry out an experiment with a real dataset to show its effectiveness for sporadic, frequent, and continuous service use cases. Country unknown/Code not availablehttps://doi.org/10.1109/SERVICES.2018.00022OSTI-MSA