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On the Privacy Risks of Cell-Based NAS Architectures

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conference contribution
posted on 2023-11-29, 18:22 authored by Hai HuangHai Huang, Zhikun ZhangZhikun Zhang, Yun Shen, Michael BackesMichael Backes, Qi Li, Yang ZhangYang Zhang
Existing studies on neural architecture search (NAS) mainly focus on efficiently and effectively searching for network architectures with better performance. Little progress has been made to systematically understand if the NAS-searched architectures are robust to privacy attacks while abundant work has already shown that human-designed architectures are prone to privacy attacks. In this paper, we fill this gap and systematically measure the privacy risks of NAS architectures. Leveraging the insights from our measurement study, we further explore the cell patterns of cell-based NAS architectures and evaluate how the cell patterns affect the privacy risks of NAS-searched architectures. Through extensive experiments, we shed light on how to design robust NAS architectures against privacy attacks, and also offer a general methodology to understand the hidden correlation between the NAS-searched architectures and other privacy risks.


Preferred Citation

Hai Huang, Zhikun Zhang, Yun Shen, Michael Backes, Qi Li and Yang Zhang. On the Privacy Risks of Cell-Based NAS Architectures. In: ACM Conference on Computer and Communications Security (CCS). 2022.

Primary Research Area

  • Trustworthy Information Processing

Name of Conference

ACM Conference on Computer and Communications Security (CCS)

Legacy Posted Date


Open Access Type

  • Unknown


@inproceedings{cispa_all_3796, title = "On the Privacy Risks of Cell-Based NAS Architectures", author = "Huang, Hai and Zhang, Zhikun and Shen, Yun and Backes, Michael and Li, Qi and Zhang, Yang", booktitle="{ACM Conference on Computer and Communications Security (CCS)}", year="2022", }

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