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Kanghua Mo
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2020 – today
- 2024
- [j8]Kanghua Mo
, Peigen Ye, Xiaojun Ren, Shaowei Wang, Wenjun 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
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
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
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
ESM: Selfish mining under ecological footprint. Inf. Sci. 606: 601-613 (2022) - 2021
- [j1]Kanghua Mo, Xiaozhang Liu, Teng Huang
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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