Biblio

Protecting privacy of the user location in Internet of Things (IoT) applications is a complex problem. Peer-to-peer (P2P) approach is one of the most popular techniques used to protect privacy in IoT applications, especially that use the location service. The P2P approach requires trust among peers in addition to serious cooperation. These requirements are still an open problem for this approach and its methods. In this paper, we propose an effective solution to this issue by creating a manager for the peers' reputation called R-TTP. Each peer has a new query. He has to evaluate the cooperated peer. Depending on the received result of that evaluation, the main peer will send multiple copies of the same query to multiple peers and then compare results. Moreover, we proposed another scenario to the manager of reputation by depending on Fog computing to enhance both performance and privacy. Relying on this work, a user can determine the most suitable of many available cooperating peers, while avoiding the problems of putting up with an inappropriate cooperating or uncommitted peer. The proposed method would significantly contribute to developing most of the privacy techniques in the location-based services. We implemented the main functions of the proposed method to confirm its effectiveness, applicability, and ease of application.

As a result of the importance of privacy at present, especially with the modern applications and technologies that have spread in the last decade, many techniques and methods have appeared to preserve privacy and protect users' data from tracking, profiling, or identification. The most popular of these technologies are those which rely on peer-to-peer or third-party cooperation. But, by reviewing a significant portion of existing research articles related to privacy, we find considerable confusion amongst several concepts and ways of protection, such as the concept of cloak area, Anonymizer, cooperation, and Third Party Peers (TTP). In this research, we revisit and review these approaches, which contain an overlap between them to distinguish each one clearly with the help of graphs and to remove their ambiguity. In this way, we shall be able provide a ready-reckoner to those interested in this field to easily differentiate between them and thus work to develop them and provide new methods. In other words, this research seeks to enhance the privacy and security in smart applications and technologies in the IoT and smart city environments.