Abstract
Internet of Things (IoT) is now serving as a vehicle to a huge number of applications, resulting in innovative and smart solutions in many fields. While providing abundant benefits which improve the quality of our lives, the IoT environment has also created new challenges, especially to users' privacy. Many IoT applications use location-based services (LBS), where service provider (SP) trust cannot be taken for granted. Sensitive information available to SPs could be used to cause considerable loss or damage to users' property or even endanger their lives. There are several methods to preserve the privacy of users' data from SPs but they all suffer from one or more anomalies. This research presents a new method, known as the Swapping of Peers and Fogs (SPF), to protect users' privacy from SPs. By exploiting the features of fogs and smart dummies, the SPF approach offers remarkable improvements to the level of protection of users' identity, which can be used to extract personal information. The SPF method does not compromise accuracy and, by using a pair of caches and fogs, provides greater efficiency for applications as compared to the existing approaches. To demonstrate the effectiveness and efficiency of the proposed method, detailed comparisons with current methods are presented via simulations based on different scenarios. Finally, an application of the SPF method to connected street systems in smart cities is also discussed.