Jul 2026· International Journal of Machine Learning and Cybernetics· Vol 17· 0 citations· 65 references
Computer Science
TL;DR
This research introduces a new graph adversarial attack protection approach termed evolutionary algorithm integration of neighbor importance estimate to tackle this issue and attains notably superior performance in comparison to alternative defense methodologies.
An active paradigm that repurposes the offensive tactic of node injection into a structural defense, ANIE significantly enhances GNN robustness, outperforming state-of-the-art defenses by up to 2× in classification accuracy under poisoning and evasion attacks.
Xiangchao Wen, Zhen Liu, Yunfei Liu· Proceedings of the 32nd ACM...· 0 citations
A novel Target-aware Interaction-guided Reinforcement learning for Black-box node injection Attacks on GNNs (TIRBA), which formulates the attack as a Markov Decision Process and jointly optimizes node feature generation and edge construction in a heterogeneous action space.
By integrating temporal graph construction, adversarial augmentation, and GCN classification, GraphGAN effectively models coordinated attack behaviors and mitigates class imbalance, providing a robust and topology-aware solution for intrusion detection in data-constrained environments.
Mohammad Arif Hossain, Yeahia Sarker, Md Jafrin Hossain et al.· 0 citations
This work proposes GraphRP (Graph Reprogramming Protection), a proactive defense framework that repurposes Model Reprogramming for security, and proves a lower bound on the attacker's estimation error that increases with the structural sensitivity of the reprogramming noise.
Yan Wen, Zhenyi Wang, Heng Huang· Proceedings of the 32nd ACM...· 0 citations
This work designs a dual-consistency graph augmentation method that enriches the graph topology to mitigate structural vulnerabilities and presents an adversarial masked autoen-coder to mitigate model overfitting to the perturbed graph.
Qi-Qi Zhang, Chuan-Jin Liu, Gen Liu et al.· Proceedings of the Thirty-Fi...· 0 citations
The proposed Collateral Damage Constrained Graph Backdoor Attack (CDCA) combines neighborhood-aware target node selection with a self-constrained trigger generation strategy to suppress trigger-induced propagation by enforcing prediction consistency on clean K -hop neighboring nodes.
Di Jin, Ze-Chuan Zhang, Bing-Dao Feng et al.· Proceedings of the Thirty-Fi...· 0 citations
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