Security monitoring method for ICS based on information gain ratio and maximum entropy model
文献类型：会议论文
| 作者 | Li SG(李声刚)2,3,4; Shang WL(尚文利)3,4 ; Chen CY(陈春雨)3,4; Lu, Yan1; Dong, Zhiwei1; Xu, Ye2
|
| 出版日期 | 2020 |
| 会议日期 | November 6-8, 2020 |
| 会议地点 | Shanghai, China |
| 关键词 | Industrial control system Information gain ratio Maximum entropy model Security monitoring |
| 页码 | 2272-2277 |
| 英文摘要 | In today's information age, in order to meet the requirement of high efficiency outlier detection in the production process of industrial control system, the intrusion characteristics are analyzed and warned in time to prevent from happening. An intrusion detection scheme (IGR-MEM) based on information gain ratio feature selection and maximum entropy model is proposed. The collected industrial control data are normalized and a new information gain ratio feature selection method considering feature correlation and redundancy is proposed to choose the best feature subset from the network connection data. According to the extracted training sample feature subset, the maximum entropy model is devoted to construct the classifier, and finally the trained classifier is applied for intrusion detection. The test results express that the IGR-MEM scheme is able to select the best feature collection, improve the detection efficiency, and improve the accuracy of ICS security monitoring and reduce the false alarm rate compared with other algorithms. |
| 产权排序 | 1 |
| 会议录 | Proceedings - 2020 Chinese Automation Congress, CAC 2020
 |
| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISBN号 | 978-1-7281-7687-1 |
| WOS记录号 | WOS:000678697002063 |
| 源URL | [http://ir.sia.cn/handle/173321/28366]  |
| 专题 | 沈阳自动化研究所_工业控制网络与系统研究室 |
| 通讯作者 | Shang WL(尚文利) |
| 作者单位 | 1.State Grid Liaoning Electric Power Company Limited Electric Power Research Institute, Power Grid Technology Center, Shenyang 110006, China 2.Shenyang Ligong University, School of Automation and Electrical Engineering 3.Shenyang Institute of Automation, Chinese Academy of Sciences 4.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, China |
| 推荐引用方式 GB/T 7714 | Li SG,Shang WL,Chen CY,et al. Security monitoring method for ICS based on information gain ratio and maximum entropy model[C]. 见:. Shanghai, China. November 6-8, 2020. |
入库方式： OAI收割
来源：沈阳自动化研究所
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