Abstract
While social networking sites gain massive popularity for their friendship networks, user privacy issues arise due to the incorporation of location-based services (LBS) into the system. Preferential LBS takes a user’s social profile along with their location to generate personalized recommender systems. With the availability of the user’s profile and location history, we often reveal sensitive information to unwanted parties. Hence, providing location privacy to such preferential LBS requests has become crucial. However, the current technologies focus on anonymizing the location through granularity generalization. Such systems, although provides the required privacy, come at the cost of losing accurate recommendations. Hence, in this paper, we propose a novel location privacy-preserving mechanism that provides location privacy through k-anonymity and provides the most accurate results. Experimental results that focus on mobile users and context-aware LBS requests prove that the proposed method performs superior to the existing methods.
Highlights
Online Social Network (OSN) has become an inevitable part of our lives
We have considered only users from the USA, and all the cities and universities belong to the USA
As the location-based searches are moving towards context awareness to provide the user with a better experience, we tend to lose the user’s personal information
Summary
Online Social Network (OSN) has become an inevitable part of our lives. We use them to connect with people and find new places, things, news, games, and many more. As OSN has become a one-stop-shop for any information, they have found their spot on our mobile phones to ease the access. Such applications are called mobile social networks (MSN), and they have been a huge hit ever since they were introduced. It is expected that the number of users who use MSN reaches around 2.46 billion in 2017 and 3.02 billion in 2021. This number is almost onethird of the current earth’s population. One of the significant advantages of MSN is its access to precise location information. This information is used for various purposes like geotagging, augmented reality, and location-based services
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