@Article{cmc.2020.05825,
AUTHOR = {Yabin Xu, Xuyang Meng, Yangyang Li, Xiaowei Xu},
TITLE = {Research on Privacy Disclosure Detection Method in Social Networks Based on Multi-Dimensional Deep Learning},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {62},
YEAR = {2020},
NUMBER = {1},
PAGES = {137--155},
URL = {http://www.techscience.com/cmc/v62n1/38104},
ISSN = {1546-2226},
ABSTRACT = {In order to effectively detect the privacy that may be leaked through social
networks and avoid unnecessary harm to users, this paper takes microblog as the research
object to study the detection of privacy disclosure in social networks. First, we perform
fast privacy leak detection on the currently published text based on the fastText model. In
the case that the text to be published contains certain private information, we fully
consider the aggregation effect of the private information leaked by different channels,
and establish a convolution neural network model based on multi-dimensional features
(MF-CNN) to detect privacy disclosure comprehensively and accurately. The
experimental results show that the proposed method has a higher accuracy of privacy
disclosure detection and can meet the real-time requirements of detection.},
DOI = {10.32604/cmc.2020.05825}
}