Kanghua Mo

According to our database, Kanghua Mo authored at least 17 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

TransLock: Securing LLM deployment for software applications via self-locking watermarks.

Pei-Gen Ye, Zhenxin Zhang, Kanghua Mo, Yun Peng

Empir. Softw. Eng., April, 2026

Your Non-Transferable Learning is Fragile: Practical Breach of Protected Models.

Anli Yan, Huali Ren, Kanghua Mo, Pei-Gen Ye, Zhenxin Zhang, Hongyang Yan, Jin Li

IEEE Trans. Inf. Forensics Secur., 2026

HPA: Manipulating deep reinforcement learning via adversarial interaction.

Kanghua Mo, Zhengxin Zhang, Yuanzhi Zhang, Yucheng Long, Zhengdao Li

J. Syst. Archit., 2026

2025

Attractive Metadata Attack: Inducing LLM Agents to Invoke Malicious Tools.

Kanghua Mo, Li Hu, Yucheng Long, Zhihao Li

CoRR, August, 2025

Inverse correction-optimized vertical federated unlearning.

Lang Li, Li Hu, Kanghua Mo, Ziyu Ding, Yaqi Wu, Hongyang Yan, Jin Li

J. Supercomput., May, 2025

Enhancing Model Intellectual Property Protection With Robustness Fingerprint Technology.

Anli Yan, Huali Ren, Kanghua Mo, Zhenxin Zhang, Shaowei Wang, Jin Li

IEEE Trans. Inf. Forensics Secur., 2025

Distraction is All You Need for Multimodal Large Language Model Jailbreaking.

Zuopeng Yang, Jiluan Fan, Anli Yan, Erdun Gao, Xin Lin, Tao Li, Kanghua Mo, Changyu Dong

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024

Security and Privacy Issues in Deep Reinforcement Learning: Threats and Countermeasures.

Kanghua Mo, Peigen Ye, Xiaojun Ren, Shaowei Wang, Wenjun Li, Jin Li

ACM Comput. Surv., June, 2024

Exploring the vulnerability of self-supervised monocular depth estimation models.

Ruitao Hou, Kanghua Mo, Yucheng Long, Ning Li, Yuan Rao

Inf. Sci., 2024

2023

Empirical study of privacy inference attack against deep reinforcement learning models.

Huaicheng Zhou, Kanghua Mo, Teng Huang, Yongjin Li

Connect. Sci., December, 2023

Attacking Deep Reinforcement Learning With Decoupled Adversarial Policy.

Kanghua Mo, Weixuan Tang, Jin Li, Xu Yuan

IEEE Trans. Dependable Secur. Comput., 2023

Decision Poisson: From Universal Gravitation to Offline Reinforcement Learning.

Heqiu Cai, Zhanao Zhang, Zhicong Yao, Kanghua Mo, Dixuan Chen, Hongyang Yan

Proceedings of the Artificial Intelligence Security and Privacy, 2023

2022

Sender anonymity: Applying ring signature in gateway-based blockchain for IoT is not enough.

Arthur Sandor Voundi Koe, Shan Ai, Pengfei Huang, Anli Yan, Juan Tang, Qi Chen, Kanghua Mo, Wanqing Jie, Shiwen Zhang

Inf. Sci., 2022

ESM: Selfish mining under ecological footprint.

Shan Ai, Guoyu Yang, Chang Chen, Kanghua Mo, Wangyong Lv, Arthur Sandor Voundi Koe

Inf. Sci., 2022

An efficient adversarial example generation algorithm based on an accelerated gradient iterative fast gradient.

Jiabao Liu, Qixiang Zhang, Kanghua Mo, Xiaoyu Xiang, Jin Li, Debin Cheng, Rui Gao, Beishui Liu, Kongyang Chen, Guanjie Wei

Comput. Stand. Interfaces, 2022

2021

Querying little is enough: Model inversion attack via latent information.

Kanghua Mo, Xiaozhang Liu, Teng Huang, Anli Yan

Int. J. Intell. Syst., 2021

2020

Querying Little Is Enough: Model Inversion Attack via Latent Information.

Kanghua Mo, Teng Huang, Xiaoyu Xiang

Proceedings of the Machine Learning for Cyber Security - Third International Conference, 2020