Research on KNN Algorithm of Charging Device Based on Attack Recognition Method

Author:

Huang Zhiwei,Yan Xichao,Wang Qiangang,Chen Yuansheng,Wu Wenju,Zhan Jiewen,Chen Rui,Ding Kai,Zu Lianxing,Xu Aijun,Su Zongzhou,Chen Dianjun,Lin Sajia,Xu Peng,Wang Chong

Abstract

Abstract With the continuous improvement of the level of economic development and the increasingly serious environmental problems, new energy is gradually being respected by people, and more and more electric vehicles have been put on the market and gradually used widely. The development of electric vehicles has led to the development of charging devices. However, traditional charging devices operate in an open environment, and communication with other devices depends on information interaction with the network. With the development of network information today, network attacks are ubiquitous, and there are various risks in network information interaction. As long as there is a security loophole in the charging device, an attacker can use various means to attack the device and even invade the inside of the power grid, which directly affects the safe and stable operation of the power grid. Aiming at the potential threats in operation, a research on the nearest neighbor algorithm of charging device K based on attack recognition method is proposed here to improve the information security and operation reliability of charging device.

Publisher

IOP Publishing

Subject

General Physics and Astronomy

Reference20 articles.

1. An overview of electric vehicle technology;Chan;Proceedings of the IEEE

2. Wireless power transfer for electric vehicle applications;Li;Emerging and Selected Topics in Power Electronics, IEEE Journal of,2015

3. Advanced concepts in electric vehicle design;Shimizu;IEEE Transactions on Industrial Electronics,1997

4. Engineering the EV future

5. Optimal planning of electric-vehicle charging stations in distribution systems;Liu;IEEE Transactions on Power Delivery,2013

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