Ning Wang - RankMe

33 papers A* 3A 3B 4C 1Journal 14Unranked 7

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Beyond Uniformity: Robust Backdoor Attacks on Deep Neural Networks with Trigger Selection. PAKDD (6) Shixiong Li, Xingyu Lyu, Ning Wang, Tao Li, Danjue Chen, Yimin Chen
2025	A	`conf`	BoBa: Boosting Backdoor Detection Through Data Distribution Inference in Federated Learning. ECAI Zhengyuan Jiang, Xingyu Lyu, Shanghao Shi, Yang Xiao, Yimin Chen, Y. Thomas Hou, Wenjing Lou, Ning Wang
2025	B	`conf`	Buffer is All You Need: Defending Federated Learning against Backdoor Attacks under Non-iids via Buffering. TrustCom Xingyu Lyu, Ning Wang, Yang Xiao, Shixiong Li, Tao Li, Danjue Chen, Yimin Chen
2025	J	`jnl`	Buffer is All You Need: Defending Federated Learning against Backdoor Attacks under Non-iids via Buffering. CoRR Xingyu Lyu, Ning Wang, Yang Xiao, Shixiong Li, Tao Li, Danjue Chen, Yimin Chen
2025	J	`jnl`	FLARE: Defending Federated Learning Against Model Poisoning Attacks via Latent Space Representations. IEEE Trans. Dependable Secur. Comput. Ning Wang, Chaoyu Zhang, Yang Xiao, Yimin Chen, Wenjing Lou, Y. Thomas Hou
2025	J	`jnl`	FeCo: Boosting Intrusion Detection Capability in IoT Networks via Contrastive Learning. IEEE Trans. Dependable Secur. Comput. Ning Wang, Shanghao Shi, Yimin Chen, Wenjing Lou, Y. Thomas Hou
2025	—	`conf`	Let the Noise Speak: Harnessing Noise for a Unified Defense Against Adversarial and Backdoor Attacks. ESORICS (1) Md Hasan Shahriar, Ning Wang, Naren Ramakrishnan, Y. Thomas Hou, Wenjing Lou
2025	A*	`conf`	Scale-MIA: A Scalable Model Inversion Attack against Secure Federated Learning via Latent Space Reconstruction. NDSS Shanghao Shi, Ning Wang, Yang Xiao, Chaoyu Zhang, Yi Shi, Y. Thomas Hou, Wenjing Lou
2025	J	`jnl`	Two Heads Are Better than One: Model-Weight and Latent-Space Analysis for Federated Learning on Non-iid Data against Poisoning Attacks. CoRR Xingyu Lyu, Ning Wang, Yang Xiao, Shixiong Li, Tao Li, Danjue Chen, Yimin Chen
2024	J	`jnl`	BoBa: Boosting Backdoor Detection through Data Distribution Inference in Federated Learning. CoRR Ning Wang, Shanghao Shi, Yang Xiao, Yimin Chen, Y. Thomas Hou, Wenjing Lou
2024	B	`conf`	Hermes: Boosting the Performance of Machine-Learning-Based Intrusion Detection System through Geometric Feature Learning. MobiHoc Chaoyu Zhang, Shanghao Shi, Ning Wang, Xiangxiang Xu, Shaoyu Li, Lizhong Zheng, Randy C. Marchany, Mark Gardner, Y. Thomas Hou, Wenjing Lou
2024	J	`jnl`	NoiSec: Harnessing Noise for Security against Adversarial and Backdoor Attacks. CoRR Md Hasan Shahriar, Ning Wang, Y. Thomas Hou, Wenjing Lou
2023	—	`—`	Building trustworthy machine learning systems in adversarial environments. Ning Wang
2023	J	`jnl`	MANDA: On Adversarial Example Detection for Network Intrusion Detection System. IEEE Trans. Dependable Secur. Comput. Ning Wang, Yimin Chen, Yang Xiao, Yang Hu, Wenjing Lou, Y. Thomas Hou
2023	—	`conf`	MINDFL: Mitigating the Impact of Imbalanced and Noisy-labeled Data in Federated Learning with Quality and Fairness-Aware Client Selection. MILCOM Chaoyu Zhang, Ning Wang, Shanghao Shi, Changlai Du, Wenjing Lou, Y. Thomas Hou
2023	J	`jnl`	Scale-MIA: A Scalable Model Inversion Attack against Secure Federated Learning via Latent Space Reconstruction. CoRR Shanghao Shi, Ning Wang, Yang Xiao, Chaoyu Zhang, Yi Shi, Y. Thomas Hou, Wenjing Lou
2022	A	`conf`	FLARE: Defending Federated Learning against Model Poisoning Attacks via Latent Space Representations. AsiaCCS Ning Wang, Yang Xiao, Yimin Chen, Yang Hu, Wenjing Lou, Y. Thomas Hou
2022	A*	`conf`	FeCo: Boosting Intrusion Detection Capability in IoT Networks via Contrastive Learning. INFOCOM Ning Wang, Yimin Chen, Yang Hu, Wenjing Lou, Y. Thomas Hou
2022	A	`conf`	Squeezing More Utility via Adaptive Clipping on Differentially Private Gradients in Federated Meta-Learning. ACSAC Ning Wang, Yang Xiao, Yimin Chen, Ning Zhang, Wenjing Lou, Y. Thomas Hou
2022	—	`conf`	Transferability of Adversarial Examples in Machine Learning-based Malware Detection. CNS Yang Hu, Ning Wang, Yimin Chen, Wenjing Lou, Y. Thomas Hou
2021	A*	`conf`	MANDA: On Adversarial Example Detection for Network Intrusion Detection System. INFOCOM Ning Wang, Yimin Chen, Yang Hu, Wenjing Lou, Y. Thomas Hou
2019	—	`conf`	PriRoster: Privacy-preserving Radio Context Attestation in Cognitive Radio Networks. DySPAN Ruide Zhang, Ning Wang, Ning Zhang, Zheng Yan, Wenjing Lou, Y. Thomas Hou
2018	J	`jnl`	Energy Efficiency Maximization for CoMP Joint Transmission with Non-Ideal Power Amplifiers. CoRR Yuhao Zhang, Qimei Cui, Ning Wang
2018	J	`jnl`	Energy-Efficient User Access Control and Resource Allocation in HCNs with Non-Ideal Circuitry. CoRR Yuhao Zhang, Qimei Cui, Ning Wang
2018	J	`jnl`	Energy-efficient resource allocation for hybrid bursty services in multi-relay OFDM networks. CoRR Yuhao Zhang, Qimei Cui, Ning Wang, Yanzhao Hou, Weiliang Xie
2018	J	`jnl`	Optimal Pilot Symbols Ratio in terms of Spectrum and Energy Efficiency in Uplink CoMP Networks. CoRR Yuhao Zhang, Qimei Cui, Ning Wang
2018	C	`conf`	Optimization Deployment of Roadside Units with Mobile Vehicle Data Analytics. APCC Xuemei Cao, Qimei Cui, Sihai Zhang, Xueying Jiang, Ning Wang
2018	J	`jnl`	Vehicle Distributions in Large and Small Cities: Spatial Models and Applications. IEEE Trans. Veh. Technol. Qimei Cui, Ning Wang, Martin Haenggi
2017	B	`conf`	Energy efficiency maximization for CoMP joint transmission with non-ideal power amplifiers. PIMRC Yuhao Zhang, Qimei Cui, Ning Wang
2017	J	`jnl`	Energy-efficient resource allocation for hybrid bursty services in multi-relay OFDM networks. Sci. China Inf. Sci. Yuhao Zhang, Qimei Cui, Ning Wang, Yanzhao Hou, Weiliang Xie
2017	—	`conf`	Energy-efficient user access control and resource allocation in HCNs with non-ideal circuitry. WCSP Yuhao Zhang, Qimei Cui, Ning Wang
2017	—	`conf`	Optimal Pilot Symbols Ratio in Terms of Spectrum and Energy Efficiency in Uplink CoMP Networks. VTC Spring Yuhao Zhang, Qimei Cui, Ning Wang
2017	B	`conf`	Spatial Point Process Modeling of Vehicles in Large and Small Cities. GLOBECOM Qimei Cui, Ning Wang, Martin Haenggi