典型文献
TPRPF:a preserving framework of privacy relations based on adversarial training for texts in big data
文献摘要：
1 Introduction
Texts data are used to train deep learning models in cloud servers that have the strong computing power and large storage space,which can seriously endanger the user's privacy.Specifically,the attacker can use the intercepted text representations of text data of the primary learning tasks to train an adversarial classifier to infer private attributes or private information,such as gender,age of the user,and the relation between users.
文献关键词：
中图分类号：
作者姓名：
Yuhan CHAI;Zhe SUN;Jing QIU;Lihua YIN;Zhihong TIAN
作者机构：
Cyberspace Institute of Advanced Technology,Guangzhou University,Guangzhou 510006,China
文献出处：
引用格式：
[1]Yuhan CHAI;Zhe SUN;Jing QIU;Lihua YIN;Zhihong TIAN-.TPRPF:a preserving framework of privacy relations based on adversarial training for texts in big data)[J].计算机科学前沿,2022(04):226-228
A类：
TPRPF,
Texts
B类：
preserving,framework,privacy,relations,adversarial,training,texts,big,data,Introduction,are,used,deep,learning,models,cloud,servers,that,have,strong,computing,power,large,storage,space,which,can,seriously,endanger,Specifically,attacker,intercepted,representations,primary,tasks,classifier,infer,private,attributes,information,such,gender,between,users
AB值：
0.592466
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机标中图分类号，由域田数据科技根据网络公开资料自动分析生成，仅供学习研究参考。
