ABSTRACT
Location-based services (LBS) provide useful information about the area around a user without requiring the user to input his/her location to identify the location. The continuing rise of mobile devices sales, LBS have become popular since it provides useful services including travel information, store locators, proximity-based marketing, local news and mobile workforce management. However, there are major privacy threats because an adversary can track a user, which leads to leak personal information about the user. In order to protect privacy, the concept of location k-anonymity has been proposed. Under location k-anonymity, location is generalized into a region, called a generalized region (GR), with at least k people in it. As a result, the adversary cannot identify the query issuer among those users inside the GR, and thus, location privacy is protected. There are several location k-anonymity models under different assumptions, and this chapter introduces those models.
