Privacy Protection of Employer Location based on Casper Query Processing

Abstract

Protection of location privacy is often an essential requirement for any new or established business organization. When a new store is being set up, the owners may want to protect their exact location in order to prevent their competitors setting up their stores in a nearby location and attracting their customer base. As a store is being set up in a particular location, the owner may want to recruit new employees to work for them. The potential employees of the store may in turn want to know the location of the store before joining. If the owner does not want the store location to be known to everyone, especially their competitors, he may want to opt for location privacy of his store location. The location privacy algorithm may be such that the tentative store area may be known, but not its exact location. So, the potential employees will be satis ed knowing the broader area in which the store will be located, and the competitors will not be able to pin-point the exact location of the store. Many types of location privacy algorithms have been made use of in the past. Nearly all of them deal with location privacy of individuals making queries, while driving on a busy road network (mobile users). Our algorithms will try to take a new approach and provide location privacy to employers who need them (stationary stores or empty land plots). Till date, to our knowledge, no algorithms exists dealing with anonymizing location of: (a) to be constructed stationary building, which can be a departmental store, chain cafeteria, or even a pharmacy outlet, infamous for setting up rival stores near each other. Here we propose to use the Casper framework approach which can used to provide location privacy of new store employers. This approach takes into consideration that the store has not been constructed yet and all we have to protect is the location of an empty piece of land where it is being set up. We take into account the fact that there are other empty land slots located around and nearby our slot. This method takes into account that a new store is to be built and there are many other empty available lots available for construction. The exact location is not given out in the advertisement to help protect location privacy. We further consider that other established stores of same brand is located in nearby areas. Let us consider a popular store (example, Starbucks) in a city. A new Starbucks store is to be set up in a new location. The new store will apply location privacy algorithm such that the store will be indistinguishable among other Starbucks stores and empty land plots. The prospective employees will not know that they will be working in a new Starbucks store, not an old existing one. This algorithm is applicable for both big cities and smaller towns.