Towards understanding residential privacy by analyzing users' activities in foursquare

Location-based social network systems (LBSNSs) are becoming increasingly popular. At the same time, privacy of users' information in these systems is becoming a huge concern. In LBSNSs, such as Foursquare, users' residential addresses and their check-ins at the residential venues are regarded as sensitive and private information as the exposure of such information can reveal users' home addresses and their absence from their homes. Analysis of users' activities involving residential venues in LBSNSs, therefore, provides useful insights into users' residential privacy concerns. In addition, such analysis can help researchers to better understand users' activities related to their residential privacy so as to develop better privacy protection mechanisms. In this paper, we first analyze Foursquare data to explore the following questions related to users' residential privacy: 1) how users share the addresses of the residential venues; 2) how users share their check-ins at the residential venues. Our analysis shows that users tend to be aware of their residential privacy and try to protect their personal information in Foursquare. During the data analysis, we also identify several system vulnerabilities and privacy risks that can be exploited to violate users' residential privacy in Foursquare. Such vulnerabilities and privacy risks are actually caused by the system's design flaws and users' incautious activities. Based on the results of the data analysis, we then propose a framework that includes access control and alert mechanisms to address these privacy issues.