Standout Papers

Adversarial Machine Learning for Network Intrusion Detection Systems: A Comprehensive Survey 2023 2026 2024128
  1. Adversarial Machine Learning for Network Intrusion Detection Systems: A Comprehensive Survey (2023)
    Ke He, Dong Seong Kim et al. IEEE Communications Surveys & Tutorials

Immediate Impact

6 standout
Sub-graph 1 of 3

Citing Papers

Botnets Unveiled: A Comprehensive Survey on Evolving Threats and Defense Strategies
2024 Standout
Internet of Things intrusion detection systems: a comprehensive review and future directions
2022 Standout
2 intermediate papers

Works of Ke He being referenced

Adversarial Machine Learning for Network Intrusion Detection Systems: A Comprehensive Survey
2023 Standout
A threat model‐based approach to security testing
2012

Author Peers

Author Last Decade Papers Cites
Ke He 82 142 50 95 10 197
Kriti Bhushan 118 215 84 125 13 268
Sajad Homayoun 165 169 97 76 9 208
Mohit Sewak 104 108 37 79 13 195
Mujaheed Abdullahi 62 104 47 74 9 173
Chunhua Wu 135 233 27 211 8 291
Esraa Saleh Alomari 106 176 42 125 9 214
Firdaus Afifi 101 180 50 147 8 270
Tianyi Xing 70 199 101 57 13 241
JongHyup Lee 84 96 91 79 14 209
Chaoran Li 154 138 75 152 10 293

All Works

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Rankless by CCL
2026