Ning Wang

Ning Wang

Assistant Professor at USF

Publications

2026

Learning from Textual Radiology Reports: A Benchmark Dataset for Coronary CT Angiography [PDF]
S. Balaji, Z. Liu, Z. Jiang, S. Lei, Y. Chen, Y. Xiao, S. O. Almeida, M. J. Karivelil, C. Malanga, N. Wang
64th Annual Meeting of the Association for Computational Linguistics (ACL 2026)
Hermes: Boosting the Performance of Machine-Learning-Based Intrusion Detection System Through Geometric Feature Learning [PDF]
C. Zhang, S. Shi, N. Wang, X. Xu, S. Li, L. Zheng, R. Marchany, M. Gardner, Y. T. Hou, W. Lou
IEEE Transactions on Networking
Noise, Why Cannot You Bend? Detecting Adversarial Perturbations in Wireless Sensing via Structural Fragility [PDF]
M. H. Shahriar, N. Wang, A. K. Sikder, N. Ramakrishnan, Y. T. Hou, W. Lou
AsiaCCS 2026
EarlyShield: Early-Stage Screening for Robust Personalized Federated Learning [PDF]
S. Li, X. Lyu, N. Wang, T. Li, D. Chen, Y. Hu, Y. Chen
PAKDD 2026

2025

FLARE: Defending Federated Learning Against Model Poisoning Attacks via Latent Space Representations [PDF]
N. Wang, C. Zhang, Y. Xiao, Y. Chen, W. Lou, Y. T. Hou
IEEE Transactions on Dependable and Secure Computing
FeCo: Boosting Intrusion Detection Capability in IoT Networks via Contrastive Learning [PDF]
N. Wang, S. Shi, Y. Chen, W. Lou, Y. T. Hou
IEEE Transactions on Dependable and Secure Computing
BoBa: Boosting Backdoor Detection Through Data Distribution Inference in Federated Learning [PDF]
Z. Jiang, X. Lyu, S. Shi, Y. Xiao, Y. Chen, Y. T. Hou, W. Lou, N. Wang
ECAI 2025
Let the Noise Speak: Harnessing Noise for a Unified Defense Against Adversarial and Backdoor Attacks [PDF]
M. H. Shahriar, N. Wang, N. Ramakrishnan, Y. T. Hou, W. Lou
ESORICS 2025
Scale-MIA: A Scalable Model Inversion Attack against Secure Federated Learning via Latent Space Reconstruction [PDF]
S. Shi, N. Wang, Y. Xiao, C. Zhang, Y. Shi, Y. T. Hou, W. Lou
NDSS 2025
Beyond Uniformity: Robust Backdoor Attacks on Deep Neural Networks with Trigger Selection [PDF]
S. Li, X. Lyu, N. Wang, T. Li, D. Chen, Y. Chen
PAKDD 2025
Buffer is All You Need: Defending Federated Learning against Backdoor Attacks under Non-iids via Buffering [PDF]
X. Lyu, N. Wang, Y. Xiao, S. Li, T. Li, D. Chen, Y. Chen
TrustCom 2025

2024

Hermes: Boosting the Performance of Machine-Learning-Based Intrusion Detection System through Geometric Feature Learning [PDF]
Chaoyu Zhang, Shanghao Shi, Ning Wang, Xiangxiang Xu, Shaoyu Li, Lizhong Zheng, Randy C. Marchany, Mark Gardner, Y. Thomas Hou, Wenjing Lou
MobiHoc 2024: 251-260

2023

Building Trustworthy Machine Learning Systems in Adversarial Environments [PDF]
Ning Wang
Virginia Tech, Ph.D. Dissertation
MANDA: On Adversarial Example Detection for Network Intrusion Detection System [PDF]
Ning Wang, Yimin Chen, Yang Xiao, Yang Hu, Wenjing Lou, Y. Thomas Hou
IEEE Transactions on Dependable and Secure Computing, 20(2): 1139-1153
MINDFL: Mitigating the Impact of Imbalanced and Noisy-labeled Data in Federated Learning with Quality and Fairness-Aware Client Selection [PDF]
Chaoyu Zhang, Ning Wang, Shanghao Shi, Changlai Du, Wenjing Lou, Y. Thomas Hou
MILCOM 2023: 331-338

2022

Squeezing More Utility via Adaptive Clipping on Differentially Private Gradients in Federated Meta-Learning [PDF]
Ning Wang, Yang Xiao, Yimin Chen, Ning Zhang, Wenjing Lou, Y. Thomas Hou
ACSAC 2022: 647-657
FLARE: Defending Federated Learning against Model Poisoning Attacks via Latent Space Representations [PDF]
Ning Wang, Yang Xiao, Yimin Chen, Yang Hu, Wenjing Lou, Y. Thomas Hou
AsiaCCS 2022: 946-958
Transferability of Adversarial Examples in Machine Learning-based Malware Detection [PDF]
Yang Hu, Ning Wang, Yimin Chen, Wenjing Lou, Y. Thomas Hou
CNS 2022: 28-36
FeCo: Boosting Intrusion Detection Capability in IoT Networks via Contrastive Learning [PDF]
Ning Wang, Yimin Chen, Yang Hu, Wenjing Lou, Y. Thomas Hou
INFOCOM 2022: 1409-1418

2021

MANDA: On Adversarial Example Detection for Network Intrusion Detection System [PDF]
Ning Wang, Yimin Chen, Yang Hu, Wenjing Lou, Y. Thomas Hou
INFOCOM 2021: 1-10

2019

PriRoster: Privacy-preserving Radio Context Attestation in Cognitive Radio Networks [PDF]
Ruide Zhang, Ning Wang, Ning Zhang, Zheng Yan, Wenjing Lou, Y. Thomas Hou
DySPAN 2019: 1-10

2018

Vehicle Distributions in Large and Small Cities: Spatial Models and Applications [PDF]
Qimei Cui, Ning Wang, Martin Haenggi
IEEE Transactions on Vehicular Technology, 67(11): 10176-10189
Optimization Deployment of Roadside Units with Mobile Vehicle Data Analytics [PDF]
Xuemei Cao, Qimei Cui, Sihai Zhang, Xueying Jiang, Ning Wang
APCC 2018: 358-363

2017

Energy-efficient resource allocation for hybrid bursty services in multi-relay OFDM networks [PDF]
Yuhao Zhang, Qimei Cui, Ning Wang, Yanzhao Hou, Weiliang Xie
Science China Information Sciences, 60(10): 102304:1-102304:18
Spatial Point Process Modeling of Vehicles in Large and Small Cities [PDF]
Qimei Cui, Ning Wang, Martin Haenggi
GLOBECOM 2017: 1-7
Energy Efficiency Maximization for CoMP Joint Transmission with Non-Ideal Power Amplifiers [PDF]
Yuhao Zhang, Qimei Cui, Ning Wang
PIMRC 2017: 1-6
Optimal Pilot Symbols Ratio in Terms of Spectrum and Energy Efficiency in Uplink CoMP Networks [PDF]
Yuhao Zhang, Qimei Cui, Ning Wang
VTC Spring 2017: 1-5
Energy-efficient User Access Control and Resource Allocation in HCNs with Non-Ideal Circuitry [PDF]
Yuhao Zhang, Qimei Cui, Ning Wang
WCSP 2017: 1-6