Research on Industrial Control Anomaly Detection Based on FCM and SVM
文献类型：会议论文
| 作者 | Shang WL(尚文利)2,3 ; Cui JR(崔君荣)1,3; Song CH(宋纯贺)2,3; Zhao JM(赵剑明)2,3; Zeng P(曾鹏)2,3
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| 出版日期 | 2018 |
| 会议日期 | July 31 - August 3, 2018 |
| 会议地点 | New York |
| 关键词 | industrial control system Modbus communication protocol intrusion detection fuzzy C-means clustering supervised support vector (SVM) |
| 页码 | 218-222 |
| 英文摘要 | In order to solve the problem of virus and Trojan attacking the application layer network protocol of industrial control system, the rule of Modbus/TCP communication protocol is analyzed. An intrusion detection method based on clustering and support vector machine is proposed. The method combines unsupervised fuzzy C-means clustering (FCM) with supervised support vector (SVM) machine to calculate the distance between industrial control network communication data and cluster center. Partial data satisfying the threshold condition is further classified by support vector machine. Experimental results show that compared with the traditional intrusion detection method, this method can effectively reduce the training time and improve the classification accuracy without needing to know the class label in advance. |
| 源文献作者 | Columbia University ; IEEE ; IEEE Computer Society ; IEEE STC Smart Computing ; IEEE TCSC ; North America Chinese Talents Association |
| 产权排序 | 1 |
| 会议录 | Proceedings - 17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications and 12th IEEE International Conference on Big Data Science and Engineering, Trustcom/BigDataSE 2018
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| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISBN号 | 978-1-5386-4387-7 |
| WOS记录号 | WOS:000495072100032 |
| 源URL | [http://ir.sia.cn/handle/173321/23361]  |
| 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.School of Automation and Electrical Engineering, Shenyang Ligong University, Shenyang, China 2.University of Chinese Academy of Sciences, Beijing, China 3.Shenyang Institute of Automation, Chinese, Academy of Sciences, Shenyang, China |
| 推荐引用方式 GB/T 7714 | Shang WL,Cui JR,Song CH,et al. Research on Industrial Control Anomaly Detection Based on FCM and SVM[C]. 见:. New York. July 31 - August 3, 2018. |
入库方式： OAI收割
来源：沈阳自动化研究所
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