November 22, 2025The Computer Journal

On adversarial attack detection in intrusion detection system with graph neural network

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Authors

KZKai Zhang QLQingqing Li JNJianting Ning

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Implication

Observational analysis shows better detection accuracy using graph neural network in intrusion detection systems, indicating improved defenses against adversarial attacks.

Key Points

Graph neural network enhances detection accuracy in intrusion detection systems, improving defense mechanisms.
Intrusion detection system demonstrated significant improvements of 26.04% to 59.04% for adversarial samples, compared to classic solutions.
Assessment using the graph neural network method focuses on capturing network topology, enhancing performance.
Significance highlights potential advancements in cybersecurity by better protecting user privacy against adversarial threats.

Cite This Study

Zhang et al. (2025) studied this question.

synapsesocial.com/papers/6924e3e6c0ce034ddc34e9e7 https://doi.org/10.1093/comjnl/bxaf096

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Implication

Observational analysis shows better detection accuracy using graph neural network in intrusion detection systems, indicating improved defenses against adversarial attacks.

On adversarial attack detection in intrusion detection system with graph neural network

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Cite This Study

On adversarial attack detection in intrusion detection system with graph neural network

Discussion

Member takes

Implication

Key Points

Cite This Study

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