Standout Papers

HAST-IDS: Learning Hierarchical Spatial-Temporal Features Using Deep Neural Networks to Improve Intrus... 2017 2026 2020 2023 314
  1. HAST-IDS: Learning Hierarchical Spatial-Temporal Features Using Deep Neural Networks to Improve Intrusion Detection (2017)
    Wei Wang, Yiqiang Sheng et al. IEEE Access

Immediate Impact

59 standout
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Citing Papers

Transformers and large language models for efficient intrusion detection systems: A comprehensive survey
2025 Standout
Signature-based intrusion detection using machine learning and deep learning approaches empowered with fuzzy clustering
2025 Standout
5 intermediate papers

Works of Jinlin Wang being referenced

Using a Recurrent Neural Network and Restricted Boltzmann Machines for Malicious Traffic Detection
2018
HAST-IDS: Learning Hierarchical Spatial-Temporal Features Using Deep Neural Networks to Improve Intrusion Detection
2017 Standout

Author Peers

Author Last Decade Papers Cites
Jinlin Wang 419 364 49 193 44 523
Ditipriya Sinha 354 273 86 197 37 508
Mohamad Fadli Zolkipli 253 320 91 156 27 495
Xingang Shi 455 325 59 141 36 529
Anwar Haque 402 323 59 162 39 592
Xiaohui Kuang 204 396 79 122 36 598
Jiahai Yang 535 354 104 170 69 630
Antonios Deligiannakis 270 254 96 151 40 468
Mouhammd Alkasassbeh 335 292 110 239 41 506
Chun Shan 346 268 101 246 37 566
Xiao Chen 362 328 188 235 32 609

All Works

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2026