Stealthy graph backdoor attack based on feature trigger
Abstract Recent studies have shown that Graph Neural Networks (GNNs) are vulnerable to backdoor attacks. Embedding malicious triggers (e.g., subgraphs or features) in the graph leads to erroneous outputs. Most graph backdoor attacks focus only on the effectiveness of the attack and ignore stealth, w...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-06-01
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| Series: | Complex & Intelligent Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s40747-025-01934-5 |
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