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Zhisheng Hu
Zhisheng Hu
Student of Department of Electrical Engineering, Pennsylvania State Unviersity
Verified email at psu.edu
Title
Cited by
Cited by
Year
Reinforcement learning algorithms for adaptive cyber defense against heartbleed
M Zhu, Z Hu, P Liu
Proceedings of the first ACM workshop on moving target defense, 51-58, 2014
612014
Windranger: A directed greybox fuzzer driven by deviation basic blocks
Z Du, Y Li, Y Liu, B Mao
Proceedings of the 44th International Conference on Software Engineering …, 2022
382022
Online algorithms for adaptive cyber defense on bayesian attack graphs
Z Hu, M Zhu, P Liu
Proceedings of the 2017 Workshop on moving target defense, 99-109, 2017
292017
Sok: On the semantic ai security in autonomous driving
J Shen, N Wang, Z Wan, Y Luo, T Sato, Z Hu, X Zhang, S Guo, Z Zhong, ...
arXiv preprint arXiv:2203.05314, 2022
252022
Adaptive cyber defense against multi-stage attacks using learning-based POMDP
Z Hu, M Zhu, P Liu
ACM Transactions on Privacy and Security (TOPS) 24 (1), 1-25, 2020
252020
Coverage-based scene fuzzing for virtual autonomous driving testing
Z Hu, S Guo, Z Zhong, K Li
arXiv preprint arXiv:2106.00873, 2021
162021
Detecting multi-sensor fusion errors in advanced driver-assistance systems
Z Zhong, Z Hu, S Guo, X Zhang, Z Zhong, B Ray
proceedings of the 31st ACM SIGSOFT International Symposium on Software …, 2022
152022
On convergence rates of game theoretic reinforcement learning algorithms
Z Hu, M Zhu, P Chen, P Liu
Automatica 104, 90-101, 2019
14*2019
Detecting safety problems of multi-sensor fusion in autonomous driving
Z Zhong, Z Hu, S Guo, X Zhang, Z Zhong, B Ray
arXiv preprint arXiv:2109.06404, 2021
112021
Reinforcement learning for adaptive cyber defense against zero-day attacks
Z Hu, P Chen, M Zhu, P Liu
Adversarial and Uncertain Reasoning for Adaptive Cyber Defense: Control-and …, 2019
92019
ROPNN: Detection of ROP payloads using deep neural networks
X Li, Z Hu, Y Fu, P Chen, M Zhu, P Liu
arXiv preprint arXiv:1807.11110, 2018
92018
What you see is not what you get! thwarting just-in-time rop with chameleon
P Chen, J Xu, Z Hu, X Xing, M Zhu, B Mao, P Liu
2017 47th Annual IEEE/IFIP International Conference on Dependable Systems …, 2017
92017
Quantifying DNN model robustness to the real-world threats
Z Zhong, Z Hu, X Chen
2020 50th Annual IEEE/IFIP International Conference on Dependable Systems …, 2020
62020
Feedback control can make data structure layout randomization more cost-effective under zero-day attacks
P Chen, Z Hu, J Xu, M Zhu, P Liu
Cybersecurity 1, 1-13, 2018
62018
Disclosing the fragility problem of virtual safety testing for autonomous driving systems
Z Hu, S Guo, Z Zhong, K Li
2021 IEEE International Symposium on Software Reliability Engineering …, 2021
52021
Towards practical robustness improvement for object detection in safety-critical scenarios
Z Hu, Z Zhong
International Workshop on Deployable Machine Learning for Security Defense …, 2020
52020
A co-design adaptive defense scheme with bounded security damages against Heartbleed-like attacks
Z Hu, P Chen, M Zhu, P Liu
IEEE Transactions on Information Forensics and Security 16, 4691-4704, 2021
42021
DeepReturn: A deep neural network can learn how to detect previously-unseen ROP payloads without using any heuristics
X Li, Z Hu, H Wang, Y Fu, P Chen, M Zhu, P Liu
Journal of Computer Security 28 (5), 499-523, 2020
42020
PASS: A system-driven evaluation platform for autonomous driving safety and security
Z Hu, J Shen, S Guo, X Zhang, Z Zhong, QA Chen, K Li
NDSS Workshop on Automotive and Autonomous Vehicle Security (AutoSec), 2022
22022
MTD Techniques for Memory Protection Against Zero-Day Attacks
P Chen, Z Hu, J Xu, M Zhu, R Erbacher, S Jajodia, P Liu
Adversarial and Uncertain Reasoning for Adaptive Cyber Defense: Control-and …, 2019
12019
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