An Automated Privacy Information Detection Approach for Protecting Individual Online Social Network Users

Li, W
Wu, J
Quan, B
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Conference Contribution
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The Japanese Society for Artificial Intelligence

Massive private messages are posted by online social network users unconsciously every day, some users may face undesirable consequences. Thus, many studies have been dedicated to privacy leakage analysis. Whereas, there are very few studies detect privacy revealing for individual users. With this motivation, this paper aims to propose an automated privacy information detection approach to effectively detect and prevent privacy leakage for individual users. Based on the experimental results and case studies, the proposed model carries out a considerable performance.

Agent-based privacy protection; NLP; Deep learning
Proceedings of the Annual Conference of JSAI, 2019, Volume JSAI2019, 33rd Annual Conference, 2019, Session ID 3H3-E-3-05, Pages 3H3E305, Released June 01, 2019
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