Improved privacy preservation approaches in mobile networks for dummy generation and spatial range queries

Abstract

Location-Based Services (LBSs) have become increasingly prevalent in today’s mobile technology sector, delivering tailored information relevant to the users’ precise locations. These services grant users access to location-centric information like the proximity of hospitals, restaurants, or other points of interest, thereby facilitating routine tasks. However, such LBSs can pose significant concerns about user privacy. Consider a user querying, “What are the directions to the best cancer hospital from the current location?”. Such queries expose the user’s current location information to the LBS provider and other intermediate nodes (intruders) in the mobile network. Query location information can reveal sensitive information about the user, such as relationships, health, religion, and nightlife habits. In this thesis, we propose two improved approaches to preserve the privacy of users’ query location in the mobile environment. As the first approach, we propose an improved dummy generation approach for better privacy. In a dummy generation approach, the user sends additional dummy locations along with the user’s actual location in its query, thereby confusing the LBS provider and the other nodes. The existing approaches have the issue of generating dummies in regions with more infeasible regions (inaccessible regions). Moreover, the existing approaches do not consider the presence of time-dependent infeasible regions. For example, consider a supermarket with opening and closing times as 9am and 9pm, respectively. From 9am to 9pm, this supermarket can be considered a feasible region; otherwise, this area can be regarded as an infeasible region. Furthermore, if the intruder estimated the centre of cloaking region (CR) using the dummy locations, it would become more accessible for the intruder to know a given user’s actual location. To improve the performance, we propose an Annulus-based Gaussian Dummy Generation (AGDG) approach. AGDG introduces the concept of a virtual cloaking region to generate cloaking regions. In AGDG, unlike traditional methods, the user’s location is not fixed at a fixed distance from the centre of the cloaking region. Additionally, AGDG considers the infeasible regions and query probability in the surrounding environment when generating dummy locations. The approach also incorporates the concept of time-dependent infeasible regions and ensures that the generated dummy locations abide by these time-dependent constraints. As the second approach, we propose a cloaking-based approach to improve the privacy of spatial range queries. In distributed spatial cloaking-based approaches, the user’s query location information is cloaked using the distributed mobile network around the user (e.g., the p2p network). Existing approaches do not preserve the user’s intent privacy. For example, suppose a user queries all the cancer hospitals near her. In that case, her location and health information (searching for intent, which is about cancer hospitals) must be preserved from both LBS providers and peers in the surrounding. Moreover, the existing approaches require a large number of peers to be employed to cloak the user query location. Maintaining such structures in a highly dynamic mobile network is challenging. We propose the notion of ijkCloak framework to improve existing distributed spatial cloaking-based approaches. The ijkCloak framework introduces the notion of ijk-anonymity to protect both the user’s query location and intent information. This method divides the user’s query location information into multiple fragmented locations. This process helps keep the user’s query location private from their peers and the LBS provider. Additionally, dummy intents are sent to the LBS provider along with the user’s actual query to protect the user’s query intent. The proposed approach ijkCloak, adopts ijk-anonymity in a mobile network environment. Because of the efficiency of ijk-anonymity, this proposed method requires fewer peers to maintain user privacy, making it more practical in a highly dynamic mobile network environment. For each approach, the theoretical analyses and comprehensive experimental study exhibits its potential to preserve location privacy in different scenarios. We hope this research encourages further research and leads to the development of improved privacy preserving approaches in mobile networks.