A new model for privacy preserving sensitive Data Mining
Author:
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx5/6383183/6395857/06396017.pdf?arnumber=6396017
Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. K-Anonymization approach for privacy preservation using data perturbation techniques in data mining;Materials Today: Proceedings;2022
2. An Overview About Privacy Protection of Facebook Social Network Users Data;Advanced Intelligent Systems for Sustainable Development (AI2SD’2020);2022
3. An Investigation and Examination of Privacy for Big Data;2021 3rd International Conference on Advances in Computing, Communication Control and Networking (ICAC3N);2021-12-17
4. Differentially Private Web Browsing Trajectory over Infinite Streams;Security and Communication Networks;2021-08-04
5. An efficient clustering-based anonymization scheme for privacy-preserving data collection in IoT based healthcare services;Peer-to-Peer Networking and Applications;2021-02-21
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