Improvement of Location-based Algorithm in the Internet of Things

Location Based Services [LBS] has become an important field of research with the rapid development of Internet-based Information Technology [IOT], technology and also; everywhere that we use smartphones and social networks in our everyday lives. Although users can enjoy the flexibility, facility, facility and location-based services [LBS] with the Internet of Things, they may lose their privacy. An untrusted and malicious LBS server can track all user information by using different methods or publish personal information to a third person. In this study, we have an algorithm [DLS] to select the currently constructed location, which is an efficient preservation privacy approach, as well as the DLP's privacy policy, which is used to protect the privacy of the user's location, taking into account both. We analyze the computational costs and different requirements of the privacy of the various users and further enhance the privacy level by optimizing the DLP algorithm, which continues with extensive simulations. That has been performed the privacy level and the timing of the algorithms are compared and analyzed. Then the simulation results, indicate the privacy level of our optimized algorithm [ODLP] has increased