CISPA
Browse
cispa_all_3620.pdf (24.17 MB)

Finding MNEMON: Reviving Memories of Node Embeddings

Download (24.17 MB)
conference contribution
posted on 2023-11-29, 18:20 authored by Yun Shen, Yufei Han, Zhikun ZhangZhikun Zhang, Min ChenMin Chen, Ting Yu, Michael BackesMichael Backes, Yang ZhangYang Zhang, Gianluca Stringhini
Previous security research efforts orbiting around graphs have been exclusively focusing on either (de-)anonymizing the graphs or understanding the security and privacy issues of graph neural networks. Little attention has been paid to understand the privacy risks of integrating the output from graph embedding models (e.g., node embeddings) with complex downstream machine learning pipelines. In this paper, we fill this gap and propose a novel model-agnostic graph recovery attack that exploits the implicit graph structural information preserved in the embeddings of graph nodes. We show that an adversary can recover edges with decent accuracy by only gaining access to the node embedding matrix of the original graph without interactions with the node embedding models. We demonstrate the effectiveness and applicability of our graph recovery attack through extensive experiments.

History

Preferred Citation

Yun Shen, Yufei Han, Zhikun Zhang, Min Chen, Ting Yu, Michael Backes, Yang Zhang and Gianluca Stringhini. Finding MNEMON: Reviving Memories of Node Embeddings. 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

2022-04-25

Open Access Type

  • Green

BibTeX

@inproceedings{cispa_all_3620, title = "Finding MNEMON: Reviving Memories of Node Embeddings", author = "Shen, Yun and Han, Yufei and Zhang, Zhikun and Chen, Min and Yu, Ting and Backes, Michael and Zhang, Yang and Stringhini, Gianluca", booktitle="{ACM Conference on Computer and Communications Security (CCS)}", year="2022", }

Usage metrics

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC