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81 results on '"Zhang, Xiaojian"'

20. Power IoT security protection architecture based on zero trust framework

Author

Wang Qi, Wang Xiangqun, Fan Jie, Chen Liandong, and Zhang Xiaojian

Subjects
Scheme (programming language), 021110 strategic, defence & security studies, Authentication, business.industry, Computer science, 0211 other engineering and technologies, 020206 networking & telecommunications, Cryptography, Access control, 02 engineering and technology, Computer security, computer.software_genre, Internet security, Data exchange, 0202 electrical engineering, electronic engineering, information engineering, Isolation (database systems), Architecture, business, computer, computer.programming_language
Abstract

The construction of the power Internet of Things has led various terminals to access the corporate network on a large scale. The internal and external business interaction and data exchange are more extensive. The current security protection system is based on border isolation protection. This is difficult to meet the needs of the power Internet of Things connection and open shared services. This paper studies the application scheme of the “zero trust” typical business scenario of the power Internet of Things with “Continuous Identity Authentication and Dynamic Access Control” as the core, and designs the power internet security protection architecture based on zero trust.

Published
2021

35. A Malicious Attack Correlation Analysis Method Integrating Interaction Process of Source-Grid-Load System

Author

Zhang Rui, Zhang Xiaojian, Congcong Shi, Ziang Lu, Fei Jiaxuan, and Huang Xiuli

Subjects
Identification (information), Artificial neural network, Event (computing), Computer science, Key (cryptography), Data mining, Grid, computer.software_genre, computer
Abstract

The key to deal with cyber security threats of gird is making full use of cyber and electrical information, and improving the ability of self-adaptation and automation for malicious attack event identification. In this Paper, the malicious attack correlation analysis method integrating the interaction process of Source-Grid-Load System (SGLS) is proposed. Firstly, the electrical events and information events in the source network are uniformly preprocessed. Secondly, based on the neural network model, the fused events are trained and classified according to the attack scenarios. Thirdly, combined with electrical abnormal events, the genetic algorithm’s initialization scheme, the selection operator and cross genetic probability are improved. The association rules for different attack scenarios are automatically generated based on the classification results. Finally, the proposed method is verified to be effective in the Source-Grid-Load simulation experiment system. The method utilizes the abnormal events of the cyber layer and the electrical layer comprehensively, and improves the identification accuracy of cyber attacks, realizes automatic event classification and correlation rule generation, showing great potential in engineering application.

Published
2018

36. Infrared Small Target Detection Based on the Weighted Strengthened Local Contrast Measure.

Author

Han, Jinhui, Moradi, Saed, Faramarzi, Iman, Zhang, Honghui, Zhao, Qian, Zhang, Xiaojian, and Li, Nan

Abstract

In this letter, a weighted strengthened local contrast measure (WSLCM) algorithm for infrared (IR) small target detection is proposed, it consists of two modules, the strengthened local contrast measure (SLCM), and the weighting function. In the SLCM calculation, the ideas of matched filter and background estimation are adopted to enhance true target and suppress complex background, then both ratio and difference operations are used to calculate the SLCM. In the weighting function definition, three components are considered: the characteristics of the target, the characteristics of the background, and the difference between them. Especially, an improved regional intensity level (IRIL) algorithm is proposed to evaluate the complexity of a cell, thus it can suppress random noises better. Experiments on some real IR images show that the proposed WSLCM can achieve a better detection performance under complex background. [ABSTRACT FROM AUTHOR]

Published
2021
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37. Design of Anomaly Monitoring Framework for Source-Grid-Load Friendly Coordination System

Author

Huang Xiuli, Zhang Rui, Fan Jie, Shi Congcong, Zhang Xiaojian, and Fei Jiaxuan

Subjects
Matching (statistics), Smart grid, Terminal (electronics), Computer science, business.industry, Anomaly (physics), Security policy, Grid, business, Business operations, Automation, Computer network
Abstract

At present, the Source-Grid-Load Friendly Coordination System is relatively weak in dealing with professional organized complex attack. To deal with the security problem, this paper designs anomaly monitoring framework of Source-Grid-Load Friendly Coordination System which includes the network communication anomaly monitoring and the Source-Grid-Load interactive terminal anomaly monitoring. For the network communication anomaly monitoring, a method based on rule-matching is used to identify anomaly events of the sensitive business operation, detecting business command exceptions by analyzing the business command features of the system. For the Source-Grid-Load interactive terminal anomaly monitoring, a method based on the security policy is used to monitor the anomaly status of the terminal by matching malicious behavior in real time.

Published
2018

42. A bio-inspired geomagnetic navigation model based on course constraint strategy under anomalies field disturbing for AUV

Author

Kun Liu, Zhang Xiaojian, Mingyong Liu, and Hong Li

Subjects
education.field_of_study, business.industry, Population, Field (computer science), Course (navigation), Constraint (information theory), Geography, Earth's magnetic field, Control theory, Convergence (routing), Magnetotaxis, Artificial intelligence, business, Evolution strategy, education
Abstract

The bio-inspired geomagnetic navigation is inspired from animals navigation behavior which dispense with the priori geomagnetic data. It can be employed by AUV for a navigation task that arrived to targeting point which is characterized with geomagnetic multi-parameter through magnetotaxis searching behavior. However, the geomagnetic anomalies area could form an extreme value region and disturb the magnetotaxis behavior to make AUV lost in the navigation space. This paper proposes an improved navigation model using a course constraint strategy to force AUV escaping from extreme value region. Firstly, we generalize disturbance to navigation process as a problem of population prematurity in evolution algorithm. The behavior constraints strategy is designed in order to avoid the prematurity of the population, forcing the AUV perform a specific action, expanding the scope of the exploration, thus bypass the abnormal area. Then, the statistics characteristics of magnetotaxis and convergence state of multi-objective functions are utilized to construct the trigger and termination conditions of behavioral constraints, and better historical data of magnetotaxis is taken as the constraint course. The evolution population is updated with the movement of vehicle and finally leads the vehicle to get to the destination potion. Finally, compared the present model with probability evolution strategy. The simulation results show that this method can effectively overcome the abnormal disturbance to the bio-inspired geomagnetic navigation and enhance the success rate of autonomous long-distance navigation.

Published
2016

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