De-Anonymizing Social Networks With Random Forest Classifier

De-Anonymizing Social Networks With Random Forest Classifier

Personal privacy is facing severe threats as social networks are sharing user data with advertisers, application developers, and data mining researchers. Although these data are anonymized by removing personal information, such as user identity, nickname, or address information, personal information...

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Bibliographic Details
Main Authors: Jiangtao Ma, Yaqiong Qiao, Guangwu Hu, Yongzhong Huang, Arun Kumar Sangaiah, Chaoqin Zhang, Yanjun Wang, Rui Zhang
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
De-anonymization
graph partition
network structure
random forest
social network analysis
Online Access:https://ieeexplore.ieee.org/document/8051053/

Internet

https://ieeexplore.ieee.org/document/8051053/

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