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Kanghua Mo
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2020 – today
- 2024
- [j8]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): 152:1-152:39 (2024) - [j7]Ruitao Hou
, Kanghua Mo
, Yucheng Long, Ning Li, Yuan Rao
:
Exploring the vulnerability of self-supervised monocular depth estimation models. Inf. Sci. 677: 120874 (2024) - 2023
- [j6]Huaicheng Zhou, Kanghua Mo, Teng Huang, Yongjin Li:
Empirical study of privacy inference attack against deep reinforcement learning models. Connect. Sci. 35(1) (2023) - [j5]Kanghua Mo
, Weixuan Tang
, Jin Li
, Xu Yuan
:
Attacking Deep Reinforcement Learning With Decoupled Adversarial Policy. IEEE Trans. Dependable Secur. Comput. 20(1): 758-768 (2023) - [c2]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: 446-455 - 2022
- [j4]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: 103612 (2022) - [j3]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: 60-71 (2022) - [j2]Shan Ai, Guoyu Yang, Chang Chen
, Kanghua Mo, Wangyong Lv, Arthur Sandor Voundi Koe:
ESM: Selfish mining under ecological footprint. Inf. Sci. 606: 601-613 (2022) - 2021
- [j1]Kanghua Mo, Xiaozhang Liu, Teng Huang
, Anli Yan:
Querying little is enough: Model inversion attack via latent information. Int. J. Intell. Syst. 36(2): 681-690 (2021) - 2020
- [c1]Kanghua Mo, Teng Huang, Xiaoyu Xiang:
Querying Little Is Enough: Model Inversion Attack via Latent Information. ML4CS (2) 2020: 583-591
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