Adversarial Machine Learning for Flooding Attacks on 5G Radio Access Network Slicing

Research article (2021 IEEE International Conference on Communications Workshops (ICC Workshops), 2021) · cited 41× · AI/ML
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Adversarial Machine Learning for Flooding Attacks on 5G Radio Access Network Slicing

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Adversarial Machine Learning for Flooding Attacks on 5G Radio Access Network Slicing is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Adversarial Machine Learning for Flooding Attacks on 5G Radio Access Network Slicing. Retrieved May 24, 2026, from https://4ort.xyz/entity/adversarial-machine-learning-for-flooding-attacks-on-5g-radio-access-network-slicing
MLA “Adversarial Machine Learning for Flooding Attacks on 5G Radio Access Network Slicing.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/adversarial-machine-learning-for-flooding-attacks-on-5g-radio-access-network-slicing.
BibTeX @misc{4ortxyz_adversarial-machine-learning-for-flooding-attacks-on-5g-radio-access-network-slicing_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Adversarial Machine Learning for Flooding Attacks on 5G Radio Access Network Slicing}}, year = {2026}, url = {https://4ort.xyz/entity/adversarial-machine-learning-for-flooding-attacks-on-5g-radio-access-network-slicing}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Adversarial Machine Learning for Flooding Attacks on 5G Radio Access Network Slicing — https://4ort.xyz/entity/adversarial-machine-learning-for-flooding-attacks-on-5g-radio-access-network-slicing (retrieved 2026-05-24)

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