Survey Paper on Location Privacy Preserving and Finding Optimal Meeting Location using Secured Homomorphism

Equipped with progressive smartphones and mobile devices, today's extremely interconnected urban population is more and more addicted to these gadgets to prepare and set up their daily lives. These applications usually suppose current (or preferred) locations of individual users or a bunch of users to produce the required service, that jeopardizes their privacy, users don't essentially wish to reveal their current (or preferred) locations to the service supplier or to different, presumably untrusted, users. During this paper, we tend to propose privacy-preserving algorithms for deciding Associate in Nursing best meeting location for a bunch of users. we tend to perform a radical privacy analysis by formally quantifying privacy-loss of the projected approaches. so as to check the performance of our algorithms during a real readying, we tend to implement and take a look at their execution potency on Nokia smartphones. By means that of a targeted user-study, we tend to plan to get Associate in nursing insight into the privacy-awareness of users in location based mostly services and also the usability of the projected solutions.