Biblio

Filters: Author is Shen, Chao  [Clear All Filters]
2022-12-20
Zhan, Yike, Zheng, Baolin, Wang, Qian, Mou, Ningping, Guo, Binqing, Li, Qi, Shen, Chao, Wang, Cong.  2022.  Towards Black-Box Adversarial Attacks on Interpretable Deep Learning Systems. 2022 IEEE International Conference on Multimedia and Expo (ICME). :1–6.
Recent works have empirically shown that neural network interpretability is susceptible to malicious manipulations. However, existing attacks against Interpretable Deep Learning Systems (IDLSes) all focus on the white-box setting, which is obviously unpractical in real-world scenarios. In this paper, we make the first attempt to attack IDLSes in the decision-based black-box setting. We propose a new framework called Dual Black-box Adversarial Attack (DBAA) which can generate adversarial examples that are misclassified as the target class, yet have very similar interpretations to their benign cases. We conduct comprehensive experiments on different combinations of classifiers and interpreters to illustrate the effectiveness of DBAA. Empirical results show that in all the cases, DBAA achieves high attack success rates and Intersection over Union (IoU) scores.
2021-05-18
Shen, Chao.  2020.  Laser-based high bit-rate visible light communications and underwater optical wireless network. 2020 Photonics North (PN). :1–1.
This talk presents an overview of the latest visible light communication (VLC) and underwater wireless optical communication (UWOC) research and development from the device to the system level. The utilization of laser-based devices and systems for LiFi and underwater Internet of Things (IoT) has been discussed.
2020-05-04
Zhang, Meng, Shen, Chao, Han, Sicong.  2019.  A Compensation Control Scheme against DoS Attack for Nonlinear Cyber-Physical Systems. 2019 Chinese Control Conference (CCC). :144–149.

This paper proposes a compensation control scheme against DoS attack for nonlinear cyber-physical systems (CPSs). The dynamical process of the nonlinear CPSs are described by T-S fuzzy model that regulated by the corresponding fuzzy rules. The communication link between the controller and the actuator under consideration may be unreliable, where Denialof-Service (DoS) attack is supposed to invade the communication link randomly. To compensate the negative effect caused by DoS attack, a compensation control scheme is designed to maintain the stability of the closed-loop system. With the aid of the Lyapunov function theory, a sufficient condition is established to ensure the stochastic stability and strict dissipativity of the closed-loop system. Finally, an iterative linearization algorithm is designed to determine the controller gain and the effectiveness of the proposed approach is evaluated through simulations.