A Location Privacy Attack Based on the Location Sharing Mechanism with Erroneous Distance in Geosocial Networks Geographical social networks (GSN) is an emerging research area. For example, Foursquare, Yelp, and WeChat are all wellknown service providers in this field. These applications are also known as locationbased services (LBS). Previous studies have suggested that these locationbased services may expose user location information. In order to ensure the privacy of the userxe2x80x99s location data, the service provider may provide corresponding protection mechanisms for its applications, including spatial cloaking, fuzzy location information, etc., so that the userxe2x80x99s real location cannot be easily cracked. It has been shown that if the positioning data provided by the user is not accurate enough, it is still difficult for an attacker to obtain the userxe2x80x99s true location. Taking this factor into consideration, our attack method is divided into two stages for the entire attack process: (1) Search stage: cover the area where the targeted user is located with unit discs, and then calculate the minimum dominating set. Use the triangle positioning method to find the minimum precision disc. (2) Inference phase: Considering the existence of errors, an ErrorAdjusted Space Partition Attack Algorithm (EASPAA) was proposed during the inference phase. Improved the need for accurate distance information to be able to derive the userxe2x80x99s true location. In this study, we focus on the Location Sharing Mechanism with Maximal Coverage Limit to implement the whole attack. Experimental results show that the proposed method still can accurately infer the userxe2x80x99s real location even when there is an error in the userxe2x80x99s location information.

An Approach Based on Customized Robust Cloaked Region for Geographic Location Information Privacy Protection Locationbased services (LBS) have gained huge popularity because of the easy availability of modern mobile devices and the fast development of geographical information science (GIS). However, the lack of protection for private user positions might give rise to privacy concerns. This kind of problem is especially serious in mobile application environment because many mobile applications tend to use LBS. In this paper, we propose a new privacy preserving approach using customized robust cloaked region (RCR), depending on a peertopeer structure and the premise that users do not trust each other when sharing their geographical locations. Two algorithms are used to generate the RCR with high user density. The area of the RCR is controlled by the userxe2x80x99s demanded degree of protection. To enhance the resistance to regional background knowledge attack, we incorporate a location semantic value into each unit of the user map. According to extensive simulations, our method can effectively obfuscate a userxe2x80x99s geographical location into a highly indistinguishable region because of the disturbance of nearby users and different equally possible locations.