Privacy preserving machine unlearning for smart cities

Author:

Chen KongyangORCID,Huang Yao,Wang Yiwen,Zhang Xiaoxue,Mi Bing,Wang Yu

Funder

National Natural Science Foundation of China

Research Project of Pazhou Lab for Excellent Young Scholars

Guangzhou Basic and Applied Basic Research Foundation

Guangdong Philosophy and Social Science Planning Project

Research on the Supporting Technologies of the Metaverse in Cultural Media

Jiangsu Key Laboratory of Media Design and Software Technology

Innovation Research for the Postgraduates of Guangzhou University

Shaanxi Key Laboratory of Flight Control and Simulation Technology

Guangzhou Key Laboratory of Environmental Catalysis and Pollution Control, Guangdong University of Technology

Science Fund for Distinguished Young Scholars of Jiangxi Province

Applied Basic Research Foundation of Yunnan Province

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering

Reference44 articles.

1. A CCC, Florian T, Nicholas C, et al (2021) Label-only membership inference attacks. In: International conference on machine learning, PMLR, pp 1964–1974

2. Aditya G, Alessandro A, Stefano S (2020) Eternal sunshine of the spotless net: Selective forgetting in deep networks. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp 9304–9312

3. Ahmed S, Yang Z, Mathias H, et al (2019) Ml-leaks: Model and data independent membership inference attacks and defenses on machine learning models. In: Network and Distributed Systems Security Symposium 2019, Internet Society

4. Bang W, Xiangwen Y, Shirui P, et al (2021) Adapting membership inference attacks to gnn for graph classification: Approaches and implications. In: 2021 IEEE International Conference on Data Mining (ICDM), IEEE, pp 1421–1426

5. Blanc G, Liu Y, Lu R et al (2022) Interactions between artificial intelligence and cybersecurity to protect future networks. Annals of Telecommunications 77:727–729

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