I am an Assistant Professor in Department of Computer Science at Old Dominion University (ODU). I received the B.S. degree in Computer Science & Engineering from Lanzhou University, China, in 2011, the M.S. degree in Computer Science from the University of Louisiana at Lafayette (ULL) in 2016, and Ph.D. degree in Electrical & Computer Engineering from ODU in 2020. My research interests include cybersecurity and secure & privacy-preserved AI. I received the Mark Weiser Best Paper Award at the IEEE PERCOM 2018, IEEE INFOCOM 2019 Best In-session Presentation Award, and NSF CRII Award in 2022.

Publications

  1. L. Zhu, R. Ning, J. Li, C. Xin, and H. Wu, "SEER: Backdoor Detection for Vision-Language Models through Searching Target Text and Image Trigger Jointly", in AAAI Conference on Artificial Intelligence (AAAI), 2024. (Acceptance ratio: 23.75%).
  2. Y. Cai, Q. Zhang, R. Ning, C. Xin, and H. Wu, "MOSAIC: A Prune-and-Assemble Approach for Efficient Model Pruning in Privacy-Preserving Deep Learning", in ACM ASIA Conference on Computer and Communications Security (ASIACCS), 2024. (Acceptance ratio: 21%).
  3. R. Ning, C. Wang, X. Li, R. Gazda, and H. Wu, "BlockFed: A High-Performance and Trustworthy Blockchain-Based Federated Learning Framework", in Proceedings of the IEEE Global Communications Conference (GLOBECOM), 2023
  4. Q. Liu, H. Shen, T. Sen, and R. Ning, "Time-Series Misalignment Aware DNN Adversarial Attacks for Connected Autonomous Vehicles", in Proceedings of the IEEE International Conference on Mobile Ad Hoc and Smart Systems (MASS). 2023}
  5. R. Ning, J. Li, C. Xin, C. Wang, X, Li, J. Cho, and H. Wu, "ScanFed: Scalable and Plug‑and‑Play Backdoor Detection in Federated Learning", in Proceedings of the IEEE International Conference on Distributed Computing Systems (ICDCS), 2023. (Acceptance ratio: 18.9%).
  6. L. Zhu, R. Ning, J. Li, C. Xin, and H. Wu, "Most and Least Retrievable Images in Visual-Language Query Systems", in Proceedings of the European Conference on Computer Vision (ECCV), 2022
  7. R. Ning, C. Xin, and H. Wu, "TrojanFlow: A Neural Backdoor Attack to Deep Learning-based Network Traffic Classifiers", in Proceedings of the IEEE International Conference on Computer Communications (INFOCOM), 2022. (Acceptance ratio:19.9%, Fast track to IEEE ToN).
  8. R. Ning, J. Li, C. Xin, C. Wang, and H. Wu, "Hibernated Backdoor: A Mutual Information Empowered Backdoor Attack to Deep Neural Networks", in Proceedings of the AAAI Conference on Artificial Intelligence (AAAI, Oral), 2022. (Acceptance ratio:15%, Oral Presentation:4.7%)
  9. Y. Cai, Q. Zhang, R. Ning, C. Xin, and H. Wu, "Hunter: HE-Friendly Structured Pruning for Efficient Privacy-Preserving Deep Learning", in Proceedings of the ACM ASIA Conference on Computer and Communications Security (AsiaCCS), 2022. (Acceptance ratio: 18.4%).
  10. H, Ali, M. Ameedi, R. Ning, J. Li, H. Wu, and J. Cho, "ACADIA: Efficient and Robust Adversarial Attacks Against Deep Reinforcement Learning", in Proceedings of the IEEE Conference on Communications and Network Security (CNS), 2022
  11. L. Zhu, R. Ning, C. Xin, and H. Wu, "CLEAR: Clean-up Trigger-Free Backdoor in Neural Networks", in Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2021
  12. R. Ning, J. Li, C. Xin, and H. Wu, "Invisible Poison: A Blackbox Clean Label Backdoor Attack to Deep Neural Networks", in Proceedings of the IEEE International Conference on Computer Communications (INFOCOM), 2021. (Acceptance ratio:19.9%).
  13. L. Zhu, R. Ning, C. Wang, C. Xin, and H. Wu, "GangSweep: Sweep out Neural Backdoors by GAN", in ACM International Conference on Multimedia (MM), Seattle, WA, October 12-16 , 2020. (Acceptance ratio: 27.8%).
  14. R. Ning, C. Wang, J. Li, C. Xin, and H. Wu, "DeepMag+: Sniffing Mobile Apps in Magnetic Field through Deep Learning”, Elsevier Journal of Pervasive and Mobile Computing (PMC), 2019.
  15. R. Ning, C. Wang, C. Xin, J. Li, L. Zhu, and H. Wu, "CapJack: Capture In-Browser Crypto-jacking by Deep Capsule Network through Behavioral Analysis", in IEEE International Conference on Computer Communications (INFOCOM), Paris, France, April 29-May 2, 2019. (Acceptance ratio: 19.7%; Best In-session Presentation Award).
  16. R. Ning, C. Wang, J. Li, C. Xin, and H. Wu, "DeepMag: Sniffing Mobile Apps in Magnetic Field through Deep Convolutional Neural Networks", in IEEE International Conference on Pervasive Computing and Communication (PerCom), Athens, Greece, March 19-23, 2018. (Acceptance ratio: 16.5%; Mark Weiser Best Paper Award (1/139)).
  17. T. Phuong, R. Ning, H. Wu, and C. Xin, "Puncturable Attribute Based Encryption for Secure Data Delivery in Internet-of-Things", in IEEE International Conference on Computer Communications (INFOCOM), Honolulu, USA, April 15-19, 2018. (Acceptance ratio: 19%).
  18. L. Tung Thanh, R. Ning, D. Zhao, H. Wu and M. Bayoumi. "Optimizing the Heterogeneous Network On-Chip Design in Manycore Architectures." In IEEE International System-on-Chip Conference (SOCC), Munich, Germany, September 5-8, 2017.

Honors and Awards

Research Grants

  1. Center of Excellence in Artificial Intelligence and Machine Learning, DoD, $5.2M (My Share: $525,000), Role: Co-PI.
  2. A Holistic Evaluation Framework for Multi‑Modal AI Security and Trustworthiness on Federated IoE, CCI, $50,000, 05/2023 ‑ 05/2024. Role: PI
  3. Spotlighting and Mitigating Cyber‑Attacks in AIoT‑enabled Maritime Transportation, CCI, $100,000. Role: Co‑PI
  4. A Graduate Certificate in Web Archiving, Institute of Museum and Library Services, $100,000. Role: Co‑PI
  5. TrustAI: enhancing human confidence and trust in AI models, CCI, $60,000, 12/2022 - 12/2023. Role: PI.
  6. Facilitate the Convergence of the Next-gen AI and Wireless, Interdigital CO., $100,000, 01/2023 - 01/2024. Role: PI.
  7. IUCRC Planning Grant, NSF, $20,000, 04/2022 - 03/2023. Role: Co-PI.
  8. CRII: SaTC: Backdoor Detection, Mitigation, and Prevention in Deep Neural Networks, NSF, $175,000, 05/2022 - 04/2024. Role: Sole-PI.
  9. Blockchain-based Deep Learning Management to Enable Smart NextG Wireless Networks, CCI Secureing NextG, $100,000, 12/2021 - 08/2022. Role: PI.
  10. BlockFL: A Blockchain-based Fully Distributed Federated Learning Framework, Interdigital CO., $184,129, 01/2021 - 01/2023. Role: PI.
  11. Investigating Robustness and Uncertainty of AI Algorithms in Cyber Physical Systems, CCI Experimental Research, $50,000, 06/2021 - 05/2022. Role: PI.
  12. Comprehensive Assessment and Diagnostics for Federated AI Algorithms in Cyber Physical Systems, COVA CCI, $150,000, 07/2021 - 06/2022. Role: PI.
  13. Backdoor Detection and Mitigation in Deep Neural Networks, CCI Cybersecurity Research Collaboration Funding, COVA CCI, $200,000, 01/2021 - 12/2021. Role: Co-PI.
  14. Deep Resilience for Multifaceted Federated Learning in Internet-of-Everything, CCI, $125,000, 12/2021 - 12/2022. Role: Co-PI.
  15. CIVIIC: Cybercrime in Virginia: Impacts on Industry and Citizens, COVACCI, $150,000, 07/2021 - 06/2022. Role: Consultant.

Mentoring

Academic Services

Teaching Experience

Contact

Rui Ning
rning (at) odu.edu
Assistant Professor
Department of Computer Science
Old Dominion University
Norfolk, VA, USA