An Investigation on Detecting Bad Data Injection Attack in Smart Grid

被引:1
作者
Al-Eryani, Yasser [1 ]
Baroudi, Uthman [2 ]
机构
[1] Univ Alberta, Dept Elect & Comp Engn, Calgary, AB, Canada
[2] King Fahd Univ Petr & Minerals, Dept Comp Engn, Dhahran, Saudi Arabia
来源
2019 INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION SCIENCES (ICCIS) | 2019年
关键词
smart grid; security; state estimation; partitioning of power systems; bad data injection; APSE;
D O I
10.1109/iccisci.2019.8716414
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Security and consistency of smart grids is one of the main issues in the design and maintenance of highly controlled and monitored new power grids. Bad data injection attack could lead to disasters such as power system outage, or huge economical losses. In many attack scenarios, the attacker can come up with new attack strategies that couldn't be detected by the traditional bad data detection methods. Adaptive Partitioning State Estimation (APSE) method [3] has been proposed recently to combat such attacks. In this work, we evaluate and compare with a traditional method. The main idea of APSE is to increase the sensitivity of the chi-square test by partitioning the large grids into small ones and apply the test on each partition individually and repeat this procedure until the faulty node is located. Our simulation findings using MATPOWER program show that the method is not consistent where it is sensitive the systems size and the location of faulty nodes as well.
引用
收藏
页码:362 / 365
页数:4
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