Towards Query-limited Adversarial Attacks on Graph Neural Networks. - Haoran Li 023; Jinhong Zhang; Song Gao; Liwen Wu; Wei Zhou 011; Ruxin Wang 002 (ICTAI, 2022)

DeepLSH: A Deep Learning-based Locality Sensitive Hash Method. - Renyang Liu 001; Qiwei Dou; Haoran Li 023; Jinhong Zhang; Junhui Liu (ICDIP, 2023)

AFLOW: Developing Adversarial Examples Under Extremely Noise-Limited Settings. - Renyang Liu 001; Jinhong Zhang; Haoran Li 023; Jin Zhang; Yuanyu Wang; Wei Zhou 011 (ICICS, 2023)

Multi-scale Features Destructive Universal Adversarial Perturbations. - Huangxinyue Wu; Haoran Li 023; Jinhong Zhang; Wei Zhou 011; Lei Guo; Yunyun Dong (ICICS, 2023)

Model Inversion Attacks on Homogeneous and Heterogeneous Graph Neural Networks. - Renyang Liu 001; Wei Zhou 011; Jinhong Zhang; Xiaoyuan Liu 002; Peiyuan Si; Haoran Li 023 (SecureComm (1), 2023)

CNFA: Conditional Normalizing Flow for Query-Limited Attack. - Renyang Liu 001; Wei Zhou 011; Jinhong Zhang; Haoran Li 023; Ruxin Wang 002 (ICASSP, 2024)

Privacy-preserving and verifiable classifier training in edge-assisted mobile communication systems. - Chen Wang 042; Jian Xu 004; Haoran Li 023; Fucai Zhou; Qiang Wang 005 (Comput. Commun., 2024)

Metapath-free adversarial attacks against heterogeneous graph neural networks. - Haoran Li 023; Jian Xu 004; Long Yin; Qiang Wang 005; Yongzhen Jiang; Jingyi Liu (Inf. Sci., 2025)