Location-based services have become increasingly prevalent with the advancement in the positioning capabilities of smart devices and their emergence in social networking. In order to acquire a service, users must submit their identity, query interest and location details to service providers. Such information shared by users are accumulated continuously, stored and analyzed in order to extract the knowledge base from it. Generally, this extracted information is used by service providers to provide users with personalized services. The accumulated data have enormous market value which is found to be used for many lucrative purposes. This work presents a detailed study on the evolution of existing privacy preservation models need to preserve privacy, and the opportunities to integrate fog computing services into privacy architectures. The study proposes a fog integrated privacy preservation model exploring the benefits and open research issues in traditional models and recent integrated fog models. Future directions of fog incorporated privacy preservation models are presented. © 2020 ASTES Publishers. All rights reserved.