Selected Publications

[* indicates student supervised by me.]

  • Sabrina Perry*, Yili Jiang, Fangtian Zhong, Jiaqi Huang and Sohan Gyawali, “DynaDetect2.0: Improving Detection Accuracy of Data Poisoning Attacks,” 2024 Cyber Awareness and Research Symposium (CARS), Grand Forks, ND, USA, 2024, pp. 1-8. Overall Best Paper Award
  • Jiaqi Huang, Yili Jiang, Sohan Gyawali, Zhiguo Zhou and Fangtian Zhong, “Semi-supervised Federated Learning for Misbehavior Detection of BSMs in Vehicular Networks,” 2024 IEEE 100th Vehicular Technology Conference (VTC2024-Fall), Washington, DC, USA, 2024, pp. 1-6.
  • Fangtian Zhong, Qin Hu, Yili Jiang, Jiaqi Huang, Cheng Zhang and Dinghao Wu, “Enhancing Malware Classification via Self-Similarity Techniques,” in IEEE Transactions on Information Forensics and Security, vol. 19, pp. 7232-7244, 2024.
  • Sohan Gyawali, Jiaqi Huang and Yili Jiang, “Leveraging Explainable AI for Actionable Insights in IoT Intrusion Detection,” 2024 19th Annual System of Systems Engineering Conference (SoSE), Tacoma, WA, USA, 2024, pp. 92-97.
  • Xian Chen*, Y. Jiang, Jiaqi Huang, and Sohan Gyawali, “Poster: Machine Learning Based False Position Detection Using Data-to-Image Transformation,” In 2024 IEEE International Conference on Mobility, Operations, Services and Technologies (IEEE MOST), pp. 286-287, 2024.
  • Sabrina Perry*, Yili Jiang, Fangtian Zhong and Chong Yu, “Detecting Poisoning Attacks with DynaDetect,” in International Symposium on Intelligent Computing and Networking(ISICN 2024), San Juan, Puerto Rico, USA, March 2024.
  • Sohan Gyawali, Kaamran Sartipi, Benjamin Van Ravesteyn, Jiaqi Huang and Yili Jiang, “Enhanced and Explainable Deep Learning-Based Intrusion Detection in IoT Networks,” in 2023 IEEE Military Communications Conference (MILCOM), Boston, MA, USA, Octobor 2023.
  • Yili Jiang, Kuan Zhang, Yi Qian, and Liang Zhou, “P2AE: Preserving Privacy, Accuracy, and Efficiency in Location-dependent Mobile Crowdsensing,” in IEEE Transactions on Mobile Computing, vol. 22, no. 4, pp. 2323-2339, 2023.
  • Yili Jiang, Kuan Zhang, Yi Qian, and Liang Zhou, “Anonymous and Efficient Authentication Scheme for Privacy-preserving Distributed Learning,” in IEEE Transactions on Information Forensics and Security, vol. 17, pp. 2227-2240, 2022.
  • Yili Jiang, Kuan Zhang, Yi Qian, and Rose Qingyang Hu, “Privacy-preserving Data Deduplication in Edge-assisted Mobile Crowdsensing,” in International Journal of Multimedia Intelligence and Security, 2022, 4(1): 1-19.
  • Yili Jiang, Kuan Zhang, Yi Qian, and Liang Zhou, “Reinforcement Learning based Query Optimization in Differentially Private IoT Data Publishing,” in IEEE Internet of Things Journal, vol. 8, no. 14, pp. 11163-11176, 15 July, 2021.
  • Yili Jiang, Kuan Zhang, Yi Qian, and Rose Qingyang Hu. “Preserving Location Privacy and Accurate Task Allocation in Edge-assisted Mobile Crowdsensing”, 2022 IEEE Wireless Communications and Networking Conference (WCNC), Austin, TX, USA, 10-13 April 2022.
  • Yili Jiang, Kuan Zhang, Yi Qian, and Rose Qingyang Hu. “Cooperative Task Allocation in Edge Computing Assisted Vehicular Crowdsensing”, 2021 IEEE Global Communication Conference (Globecom’21), Madrid, Spain, 7-11 December 2021.
  • Yili Jiang, Kuan Zhang, Yi Qian, and Rose Qingyang Hu. “Efficient and Privacy-preserving Distributed Learning in Cloud-Edge Computing Systems”, in Proceedings of the 3rd ACM Workshop on Wireless Security and Machine Learning (WiseML’21). Association for Computing Machinery, New York, NY, USA, 2021, pp. 25–30.
  • Yili Jiang, Kuan Zhang, Yi Qian, and Liang Zhou, “An Optimization Framework for Privacy-preserving Access Control in Cloud-Fog Computing Systems,” 2020 IEEE 92nd Vehicular Technology Conference (VTC2020-Fall), 2020, pp. 1-5.