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For efficiently preserving user's location privacy, we propose a novel dummy location privacy-preserving (DLP) algorithm by considering both computational costs and various privacy requirements of different users.
A dummy location can be introduced for the assignment of demand that cannot be met.
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"They've got some dummy locations," an official told me.
Evaluation results show that the ADLS algorithm has a high probability of identifying the user's real location out from chosen dummy locations in the DLS algorithm.
It integrates SNS and LBS into one server, i.e., Location-storing Social Network Server (LSSNS), and uses the dummy locations and the dedicated mapping protocols between LSSNS and Cellular Tower (CT) to share privacy-preserving locations.
To protect user's privacy, Niu et al. proposed an algorithm named enhanced-Dummy Location Selection (en-DLS).
In this work, we first analyze the current dummy-location selection (DLS) algorithm an efficient location privacy preservation approach and design an attack algorithm for DLS (ADLS) for test emerging IoT security.
For fuelwood a model with location dummy [Kiwele ward (KIW) = 1] and a global model are included.
Therefore, we expect the performance of our income prediction to improve significantly if we were to add coarse location dummy variables in the feature space.
Degree days and a dummy variable indicating location in the Mediterranean area were the strongest predictors of energy efficiency while taller and leaner buildings tended to be more energy efficient.
Our estimations control for age (in years) and age squared, tenure at current job (in years) and tenure squared, education (in years), a sex dummy, an urban location dummy, household size, dummies for having a kitchen and water source outside of the dwelling, and initial labor supply.
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