Privacy‐enhancing machine learning framework with private aggregation of teacher ensembles

Author:

Zhao Shengnan12ORCID,Zhao Qi3,Zhao Chuan4,Jiang Han12,Xu Qiuliang12

Affiliation:

1. School of Software Shandong University Jinan People's Republic of China

2. Key Laboratory of Shandong Province for Software Engineering Jinan People's Republic of China

3. Nantong Rural Commerical Bank Nantong People's Republic of China

4. Quan Cheng Laboratory Jinan People's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Artificial Intelligence,Human-Computer Interaction,Theoretical Computer Science,Software

Reference39 articles.

1. YuanF ChenS LiangK XuL.Research on the coordination mechanism of traditional Chinese medicine medical record data standardization and characteristic protection under big data environment. 1 of 1. 1st ed. Shandong People's Publishing House; 2021.

2. TramèrF ZhangF JuelsA ReiterMK RistenpartT.Stealing machine learning models via prediction apis.25th {USENIX} Security Symposium ({USENIX} Security 16);2016:601‐618.

3. FredriksonM JhaS RistenpartT.Model inversion attacks that exploit confidence information and basic countermeasures.Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security;2015:1322‐1333.

4. ShokriR StronatiM SongC ShmatikovV.Membership inference attacks against machine learning models.2017 IEEE Symposium on Security and Privacy (SP).IEEE;2017:3‐18.

5. PapernotN AbadiM ErlingssonU GoodfellowI TalwarK.Semi‐supervised knowledge transfer for deep learning from private training data. In:International Conference on Learning Representations;2017.

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