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

Date
2019
Authors
Li, W
Wu, J
Quan, B
Supervisor
Item type
Conference Contribution
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
The Japanese Society for Artificial Intelligence
Abstract

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.

Description
Keywords
Agent-based privacy protection; NLP; Deep learning
Source
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
Rights statement
J-STAGE promotes "open access", which consists of (1) free access to articles and (2) specifying the scope of reuse like modification or redistribution. Over 90% of articles on J-STAGE are free to read. Articles displaying a CC license can be reused under the terms of the license.