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Privacy Disclosure Detection in Location-Based Social Network

Jiao Yongqing 1, Xu Yabin1, 2
1. Beijing Information Science & Technology University, Beijing, 100101, China
2. Beijing Key Laboratory of Internet Culture and Digital Dissemination Research, School of Computer, Beijing Information Science & Technology University, Beijing, 100101, China
Abstract—In order to avoid the issue of privacy disclosure caused by publishing information in the location-based social network (LBSN), a method for detecting privacy disclosure is proposed in this paper. Firstly, we use the Naive Bayes classification model to classify released contents. Secondly, we extract the features of privacy disclosure in released contents according to the special categories and combine with the time and location released at the same time. Finally, we use the decision tree method to determine the possible privacy disclosure. Comparing to the Native Bayes and support vector method, the result shows that the method proposed in this paper carry out the privacy disclosure detection much effectively.

Index Terms—Location-based social network; privacy disclosure detection; naive bayes; decision tree.

Cite: Jiao Yongqing and Xu Yabin, "Privacy Disclosure Detection in Location-Based Social Network," Journal of Communications, vol. 14, no. 9, pp. 779-786, 2019. Doi: 10.12720/jcm.14.9.779-786.
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