Visible to the public Biblio

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Li, Y., Ji, X., Li, C., Xu, X., Yan, W., Yan, X., Chen, Y., Xu, W..  2020.  Cross-domain Anomaly Detection for Power Industrial Control System. 2020 IEEE 10th International Conference on Electronics Information and Emergency Communication (ICEIEC). :383—386.

In recent years, artificial intelligence has been widely used in the field of network security, which has significantly improved the effect of network security analysis and detection. However, because the power industrial control system is faced with the problem of shortage of attack data, the direct deployment of the network intrusion detection system based on artificial intelligence is faced with the problems of lack of data, low precision, and high false alarm rate. To solve this problem, we propose an anomaly traffic detection method based on cross-domain knowledge transferring. By using the TrAdaBoost algorithm, we achieve a lower error rate than using LSTM alone.

Xu, X., Ruan, Z., Yang, L..  2020.  Facial Expression Recognition Based on Graph Neural Network. 2020 IEEE 5th International Conference on Image, Vision and Computing (ICIVC). :211—214.

Facial expressions are one of the most powerful, natural and immediate means for human being to present their emotions and intensions. In this paper, we present a novel method for fully automatic facial expression recognition. The facial landmarks are detected for characterizing facial expressions. A graph convolutional neural network is proposed for feature extraction and facial expression recognition classification. The experiments were performed on the three facial expression databases. The result shows that the proposed FER method can achieve good recognition accuracy up to 95.85% using the proposed method.

Xu, F., Peng, R., Zheng, T., Xu, X..  2019.  Development and Validation of Numerical Magnetic Force and Torque Model for Magnetically Levitated Actuator. IEEE Transactions on Magnetics. 55:1–9.

To decouple the multi-axis motion in the 6 degrees of freedom magnetically levitated actuators (MLAs), this paper introduces a numerical method to model the force and torque distribution. Taking advantage of the Gaussian quadrature, the concept of coil node is developed to simplify the Lorentz integral into the summation of the interaction between each magnetic node in the remanence region and each coil node in the coil region. Utilizing the coordinate transformation in the numerical method, the computation burden is independent of the position and the rotation angle of the moving part. Finally, the experimental results prove that the force and torque predicted by the numerical model are rigidly consistent with the measurement, and the force and torque in all directions are decoupled properly based on the numerical solution. Compared with the harmonic model, the numerical wrench model is more suitable for the MLAs undertaking both the translational and rotational displacements.

Zhang, S., Peng, J., Huang, K., Xu, X., Zhong, Z..  2017.  Physical layer security in IoT: A spatial-temporal perspective. 2017 9th International Conference on Wireless Communications and Signal Processing (WCSP). :1–6.
Delay and security are both highly concerned in the Internet of Things (IoT). In this paper, we set up a secure analytical framework for IoT networks to characterize the network delay performance and secrecy performance. Firstly, stochastic geometry and queueing theory are adopted to model the location of IoT devices and the temporal arrival of packets. Based on this model, a low-complexity secure on-off scheme is proposed to improve the network performance. Then, the delay performance and secrecy performance are evaluated in terms of packet delay and packet secrecy outage probability. It is demonstrated that the intensity of IoT devices arouse a tradeoff between the delay and security and the secure on-off scheme can improve the network delay performance and secrecy performance. Moreover, secrecy transmission rate is adopted to reflect the delay-security tradeoff. The analytical and simulation results show the effects of intensity of IoT devices and secure on-off scheme on the network delay performance and secrecy performance.
Xu, X., Pautasso, C., Zhu, L., Gramoli, V., Ponomarev, A., Tran, A. B., Chen, S..  2016.  The Blockchain as a Software Connector. 2016 13th Working IEEE/IFIP Conference on Software Architecture (WICSA). :182–191.

Blockchain is an emerging technology for decentralized and transactional data sharing across a large network of untrusted participants. It enables new forms of distributed software architectures, where components can find agreements on their shared states without trusting a central integration point or any particular participating components. Considering the blockchain as a software connector helps make explicitly important architectural considerations on the resulting performance and quality attributes (for example, security, privacy, scalability and sustainability) of the system. Based on our experience in several projects using blockchain, in this paper we provide rationales to support the architectural decision on whether to employ a decentralized blockchain as opposed to other software solutions, like traditional shared data storage. Additionally, we explore specific implications of using the blockchain as a software connector including design trade-offs regarding quality attributes.