2026

• [1] DFL-C: Robust Model-Consistent Decentralized Federated Learning for Mission Networks N. Wang et al. IEEE International Conference on Sensing, Communication and Networking (SECON), 2026 PDF
• [2] Noise, Why Can't You Bend? Detecting Adversarial Perturbations in Wireless Sensing via Structural Fragility N. Wang et al. ACM Asia Conference on Computer and Communications Security (AsiaCCS), 2026 PDF
• [3] Two Heads Are Better than One: Model-Weight and Latent-Space Analysis for Federated Learning on Non-iid Data against Model Poisoning Attacks N. Wang et al. Accepted, 2026 PDF

2025

• [1] Buffer is All You Need: Defending Federated Learning Against Backdoor Attacks Under Non-Iids via Buffering N. Wang et al. IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), 2025 PDF
• [2] BoBa: Boosting Backdoor Detection through Data Distribution Inference in Federated Learning N. Wang, S. Shi, Y. Xiao, Y. Chen, Y.T. Hou, W. Lou European Conference on Artificial Intelligence (ECAI), 2025 PDF
• [3] Let the Noise Speak: Harnessing Noise for a Unified Defense Against Adversarial and Backdoor Attacks M. Hasan Shahriar, N. Wang, Y.T. Hou, W. Lou European Symposium on Research in Computer Security (ESORICS), 2025 PDF
• [4] Beyond Uniformity: Robust Backdoor Attacks on Deep Neural Networks with Trigger Selection N. Wang et al. Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2025 PDF
• [5] FeCo: Boosting Intrusion Detection Capability in IoT Networks via Contrastive Learning N. Wang, Y. Chen, Y. Hu, W. Lou, Y.T. Hou IEEE Transactions on Dependable and Secure Computing (TDSC), 2025 PDF
• [6] FLARE: Defending Federated Learning against Model Poisoning Attacks via Latent Space Representations N. Wang, Y. Xiao, Y. Chen, Y. Hu, W. Lou, Y.T. Hou IEEE Transactions on Dependable and Secure Computing (TDSC), 2025 PDF
• [7] Scale-MIA: A Scalable Model Inversion Attack against Secure Federated Learning via Latent Space Reconstruction S. Shi, N. Wang, Y. Xiao, C. Zhang, Y. Shi, Y.T. Hou, W. Lou Network and Distributed System Security Symposium (NDSS), 2025 PDF

2024

• [1] BoBa: Boosting Backdoor Detection through Data Distribution Inference in Federated Learning N Wang, S Shi, Y Xiao, Y Chen, YT Hou, W Lou arXiv preprint arXiv:2407.09658 PDF
• [2] NoiSec: Harnessing Noise for Security against Adversarial and Backdoor Attacks M Hasan Shahriar, N Wang, YT Hou, W Lou arXiv e-prints, arXiv: 2406.13073 PDF

2023

• [1] Scale-mia: A scalable model inversion attack against secure federated learning via latent space reconstruction S Shi, N Wang, Y Xiao, C Zhang, Y Shi, YT Hou, W Lou arXiv preprint arXiv:2311.05808 PDF
• [2] Mindfl: Mitigating the impact of imbalanced and noisy-labeled data in federated learning with quality and fairness-aware client selection C Zhang, N Wang, S Shi, C Du, W Lou, YT Hou MILCOM 2023-2023 IEEE Military Communications Conference (MILCOM), 331-338 PDF
• [3] Building trustworthy machine learning systems in adversarial environments N Wang Virginia Tech PDF

2022

• [1] Squeezing more utility via adaptive clipping on differentially private gradients in federated meta-learning N Wang, Y Xiao, Y Chen, N Zhang, W Lou, YT Hou Proceedings of the 38th Annual Computer Security Applications Conference PDF
• [2] Transferability of adversarial examples in machine learning-based malware detection Y Hu, N Wang, Y Chen, W Lou, YT Hou 2022 IEEE Conference on Communications and Network Security (CNS), 28-36 PDF
• [3] Flare: defending federated learning against model poisoning attacks via latent space representations N Wang, Y Xiao, Y Chen, Y Hu, W Lou, YT Hou Proceedings of the 2022 ACM on Asia Conference on Computer and Communications Security PDF
• [4] FeCo: Boosting intrusion detection capability in IoT networks via contrastive learning N Wang, Y Chen, Y Hu, W Lou, YT Hou IEEE INFOCOM 2022-IEEE Conference on Computer Communications, 1409-1418 PDF
• [5] Manda: On adversarial example detection for network intrusion detection system N Wang, Y Chen, Y Xiao, Y Hu, W Lou, YT Hou IEEE Transactions on Dependable and Secure Computing 20 (2), 1139-1153 PDF

2021

• [1] MANDA: On Adversarial Example Detection for Network Intrusion Detection System N Wang, Y Chen, Y Hu, W Lou, YT Hou IEEE INFOCOM 2021 - IEEE Conference on Computer Communications, 1-10 PDF

2019

• [1] PriRoster: Privacy-preserving radio context attestation in cognitive radio networks R Zhang, N Wang, N Zhang, Z Yan, W Lou, YT Hou 2019 IEEE International Symposium on Dynamic Spectrum Access Networks PDF

2018

• [1] Optimization deployment of roadside units with mobile vehicle data analytics X Cao, Q Cui, S Zhang, X Jiang, N Wang 2018 24th Asia-Pacific Conference on Communications (APCC), 358-363 PDF
• [2] Vehicle distributions in large and small cities: Spatial models and applications Q Cui, N Wang, M Haenggi IEEE Transactions on Vehicular Technology 67 (11), 10176-10189 PDF

2017

• [1] Spatial point process modeling of vehicles in large and small cities Q Cui, N Wang, M Haenggi GLOBECOM 2017-2017 IEEE Global Communications Conference, 1-7 PDF
• [2] Energy-efficient user access control and resource allocation in HCNs with non-ideal circuitry Y Zhang, Q Cui, N Wang 2017 9th International Conference on Wireless Communications and Signal Processing PDF
• [3] Energy efficiency maximization for CoMP joint transmission with non-ideal power amplifiers Y Zhang, Q Cui, N Wang 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications PDF
• [4] Energy-efficient resource allocation for hybrid bursty services in multi-relay OFDM networks Y Zhang, Q Cui, N Wang, Y Hou, W Xie Science China Information Sciences 60, 1-18 PDF
• [5] Optimal Pilot Symbols Ratio in terms of Spectrum and Energy Efficiency in Uplink CoMP Networks Y Zhang, Q Cui, N Wang 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 1-5 PDF