Attacking Graph Neural Networks with Bit Flips: Weisfeiler and Leman Go Indifferent-Reference-Cited by-同舟云学术

Attacking Graph Neural Networks with Bit Flips: Weisfeiler and Leman Go Indifferent

Published:2024-08-24 Issue: Volume:7 Page:1428-1439
ISSN:
Container-title:Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Kummer Lorenz¹^ORCID,Moustafa Samir¹^ORCID,Schrittwieser Sebastian²^ORCID,Gansterer Wilfried³^ORCID,Kriege Nils⁴^ORCID

Affiliation:

1. Doctoral School Computer Science, University of Vienna & Faculty of Computer Science, University of Vienna, Vienna, Austria

2. Christian Doppler Laboratory for Assurance and Transparency in Software Protection, University of Vienna & Faculty of Computer Science, University of Vienna, Vienna, Austria

3. Faculty of Computer Science, University of Vienna, Vienna, Austria

4. Research Network Data Science, University of Vienna & Faculty of Computer Science, University of Vienna, Vienna, Austria

Funder

Vienna Science and Technology Fund

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3637528.3671890

Reference79 articles.

1. Anders Aamand Justin Chen Piotr Indyk Shyam Narayanan Ronitt Rubinfeld Nicholas Schiefer Sandeep Silwal and Tal Wagner. 2022. Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks. In Advances in Neural Information Processing Systems 35. 27333--27346.

2. Mohammad-Hossein Askari-Hemmat Sina Honari Lucas Rouhier Christian S. Perone Julien Cohen-Adad Yvon Savaria and Jean-Pierre David. 2019. U-net fixed-point quantization for medical image segmentation. In Large-Scale Annotation of Biomedical Data and Expert Label Synthesis (LABELS) and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention (HAL-MICCAI) International Workshops. 115--124.

3. Binary Graph Neural Networks

4. Lejla Batina, Shivam Bhasin, Dirmanto Jap, and Stjepan Picek. 2018. CSI neural network: Using side-channels to recover your artificial neural network information. CoRR, Vol. abs/2204.07697 (2018).

5. Yoshua Bengio, Nicholas Léonard, and Aaron C. Courville. 2013. Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation. CoRR, Vol. abs/1308.3432 (2013).