中国电力2017，Vol.50Issue(10)：35-40,6.DOI:10.11930/j.issn.1004-9649.201707188
基于扩展卡尔曼滤波的虚假数据攻击检测方法
Detection Method Against False Data Injection Attack Based on Extended Kalman Filter
何耀 1周聪 1郑凌月 1张维锡 1谢育轩1
作者信息
- 1. 国网四川省电力公司巴中供电公司,四川巴中636600
- 折叠
摘要
Abstract
False data injection attacks can destroy the data integrity and availability in SCADA systems,so the detection method for data security and stable operation of smart grid is of great significance.The extended Kalman filter method uses the detected data to recursively obtain the real-time state of the system,so as to achieve the purpose of effectively detecting and checking whether or not there are false data injections in the power system.In addition,this method can not only evaluate the past operating states,but also predict the minute changes of future system.Furthermore,this method can effectively identify the false data injection attack under unknown conditions of the system.IEEE-14 node and 30-node models are used as the benchmarks for detecting false data injection attacks.The results show that the proposed method not only is superior to traditional state estimation methods that fail to detect false data injection attack,but also exhibits many advantages,such as small storage capacity and easy realization.关键词
虚假数据注入攻击/智能电网/扩展卡尔曼滤波/网络攻击Key words
false data injection attack/smart grid/extended Kalman filter/cyber attack分类
信息技术与安全科学引用本文复制引用
何耀,周聪,郑凌月,张维锡,谢育轩..基于扩展卡尔曼滤波的虚假数据攻击检测方法[J].中国电力,2017,50(10):35-40,6.
