Visible to the public Biblio

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Meng, C., Zhou, L..  2020.  Big Data Encryption Technology Based on ASCII And Application On Credit Supervision. 2020 International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE). :79—82.

Big Data Platform provides business units with data platforms, data products and data services by integrating all data to fully analyze and exploit the intrinsic value of data. Data accessed by big data platforms may include many users' privacy and sensitive information, such as the user's hotel stay history, user payment information, etc., which is at risk of leakage. This paper first analyzes the risks of data leakage, then introduces in detail the theoretical basis and common methods of data desensitization technology, and finally puts forward a set of effective market subject credit supervision application based on asccii, which is committed to solving the problems of insufficient breadth and depth of data utilization for enterprises involved, the problems of lagging regulatory laws and standards, the problems of separating credit construction and market supervision business, and the credit constraints of data governance.

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Guo, H., Shen, X., Goh, W. L., Zhou, L..  2018.  Data Analysis for Anomaly Detection to Secure Rail Network. 2018 International Conference on Intelligent Rail Transportation (ICIRT). :1–5.
The security, safety and reliability of rail systems are of the utmost importance. In order to better detect and prevent anomalies, it is necessary to accurately study and analyze the network traffic and abnormal behaviors, as well as to detect and alert any anomalies if happened. This paper focuses on data analysis for anomaly detection with Wireshark and packet analysis system. An alert function is also developed to provide an alert when abnormality happens. Rail network traffic data have been captured and analyzed so that their network features are obtained and used to detect the abnormality. To improve efficiency, a packet analysis system is introduced to receive the network flow and analyze data automatically. The provision of two detection methods, i.e., the Wireshark detection and the packet analysis system together with the alert function will facilitate the timely detection of abnormality and triggering of alert in the rail network.
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Zhao, Z., Lu, W., Ma, J., Li, S., Zhou, L..  2018.  Fast Unloading Transient Recovery of Buck Converters Using Series-Inductor Auxiliary Circuit Based Sequence Switching Control. 2018 IEEE International Power Electronics and Application Conference and Exposition (PEAC). :1-5.

This paper presents a sequence switching control (SSC) scheme for buck converters with a series-inductor auxiliary circuit, aiming at improving the load transient response. During an unloading transient, the series inductor is controlled as a small equivalent inductance so as to achieve a fast transient regulation. While in the steady state, the series inductor behaves as a large inductance to reduce the output current ripple. Furthermore, on the basis of the proposed variable inductance circuit, a SSC control scheme is proposed and implemented in a digital form. With the proposed control scheme the unloading transient event is divided into n+1 sub-periods, and in each sub-period, the capacitor-charge balance principle is used to determine the switching time sequence. Furthermore, its feasibility is validated in experiment with a 12V-3.3V low-voltage high-current synchronous buck converter. Experimental results demonstrate that the voltage overshoot of the proposed SSC scheme has improved more than 74% compared to that of the time-optimal control (TOC) scheme.

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Jie, Y., Zhou, L., Ming, N., Yusheng, X., Xinli, S., Yongqiang, Z..  2018.  Integrated Reliability Analysis of Control and Information Flow in Energy Internet. 2018 2nd IEEE Conference on Energy Internet and Energy System Integration (EI2). :1—9.
In this paper, according to the electricity business process including collecting and transmitting power information and sending control instructions, a coupling model of control-communication flow is built which is composed of three main matrices: control-communication, communication-communication, communication-control incidence matrices. Furthermore, the effective path change between two communication nodes is analyzed and a calculation method of connectivity probability for information network is proposed when considering a breakdown in communication links. Then, based on Bayesian conditional probability theory, the effect of the communication interruption on the energy Internet is analyzed and the metric matrix of controllability is given under communication congestion. Several cases are given in the final of paper to verify the effectiveness of the proposed method for calculating controllability matrix by considering different link interruption scenarios. This probability index can be regarded as a quantitative measure of the controllability of the power service based on the communication transmission instructions, which can be used in the power business decision-making in order to improve the control reliability of the energy Internet.