Kanghua Mo

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 10

Top Topics

Generation Algorithm

Reinforcement Learning

Gradient Vectors

Top Venues

Int. J. Intell. Syst.

ACM Comput. Surv.

Publications

Kanghua Mo, Peigen Ye, Xiaojun Ren, Shaowei Wang, Wenjun Li, Jin Li
Security and Privacy Issues in Deep Reinforcement Learning: Threats and Countermeasures. ACM Comput. Surv. 56 (6) (2024)
Ruitao Hou, Kanghua Mo, Yucheng Long, Ning Li, Yuan Rao
Exploring the vulnerability of self-supervised monocular depth estimation models. Inf. Sci. 677 (2024)
Huaicheng Zhou, Kanghua Mo, Teng Huang, Yongjin Li
Empirical study of privacy inference attack against deep reinforcement learning models. Connect. Sci. 35 (1) (2023)
Kanghua Mo, Weixuan Tang, Jin Li, Xu Yuan
Attacking Deep Reinforcement Learning With Decoupled Adversarial Policy. IEEE Trans. Dependable Secur. Comput. 20 (1) (2023)
Heqiu Cai, Zhanao Zhang, Zhicong Yao, Kanghua Mo, Dixuan Chen, Hongyang Yan
Decision Poisson: From Universal Gravitation to Offline Reinforcement Learning. AIS&P (1) (2023)
Arthur Sandor Voundi Koe, Shan Ai, Pengfei Huang, Anli Yan, Juan Tang, Qi Chen, Kanghua Mo, Wanqing Jie, Shiwen Zhang
Sender anonymity: Applying ring signature in gateway-based blockchain for IoT is not enough. Inf. Sci. 606 (2022)
Jiabao Liu, Qixiang Zhang, Kanghua Mo, Xiaoyu Xiang, Jin Li, Debin Cheng, Rui Gao, Beishui Liu, Kongyang Chen, Guanjie Wei
An efficient adversarial example generation algorithm based on an accelerated gradient iterative fast gradient. Comput. Stand. Interfaces 82 (2022)
Shan Ai, Guoyu Yang, Chang Chen, Kanghua Mo, Wangyong Lv, Arthur Sandor Voundi Koe
ESM: Selfish mining under ecological footprint. Inf. Sci. 606 (2022)
Kanghua Mo, Xiaozhang Liu, Teng Huang, Anli Yan
Querying little is enough: Model inversion attack via latent information. Int. J. Intell. Syst. 36 (2) (2021)
Kanghua Mo, Teng Huang, Xiaoyu Xiang
Querying Little Is Enough: Model Inversion Attack via Latent Information. ML4CS (2) (2020)