UAV-CAS is a calibrated digital-twin dataset with 99k flows across 1,024 configurations for training and testing intrusion detection in UAV swarm networks.
5g-nidd: A comprehensive network intrusion detection dataset generated over 5g wireless network,
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
GenTI builds a large CTI-annotated rule corpus and an LLM pipeline that generates and validates IDPS rules, reporting 89.4% composite quality, 94.8% CTI coverage, and raising unseen-attack detection from 45% to 87.4% while cutting false positives from 8.5% to 2.3%.
citing papers explorer
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UAV-CAS: A Calibrated Digital-Twin Dataset for Intrusion Detection in UAV Swarm Networks
UAV-CAS is a calibrated digital-twin dataset with 99k flows across 1,024 configurations for training and testing intrusion detection in UAV swarm networks.
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GenTI: Benchmarking LLMs for Autonomous IDPS Rule Generation for Unseen Attacks
GenTI builds a large CTI-annotated rule corpus and an LLM pipeline that generates and validates IDPS rules, reporting 89.4% composite quality, 94.8% CTI coverage, and raising unseen-attack detection from 45% to 87.4% while cutting false positives from 8.5% to 2.3%.