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Double Behavior Characteristics for One-Class Classification Anomaly Detection in Networked Control Systems
Wan M(万明); Shang WL(尚文利); Zeng P(曾鹏)
作者部门工业控制网络与系统研究室
关键词Function Control Behavior Process Data Behavior One-class Classification Networked Control Systems
发表期刊IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
ISSN1556-6013
2017
卷号12期号:12页码:3011-3023
收录类别SCI ; EI
EI收录号20173704144361
WOS记录号WOS:000409037000014
产权排序1
资助机构National Natural Science Foundation of China (61501447)
摘要Due to the growing dependencies of information network technology, networked control systems are undergoing a severe blow of cyberattacks, and simply modeling cyberattacks is inadequate and impractical for the detection requirements, because of various vulnerabilities in these systems and the diversities of cyberattacks. Actually, a feasible viewpoint is to identify misbehaviors by constructing a normal model of industrial communication behaviors. However, one of the chief difficulties is how to completely and appropriately summarize industrial communication behaviors according to the specific communication characteristics. In view of process control and data acquisition, this paper associates industrial communication characteristics with the time sequence, and further extracts two distinct behaviors: function control behavior and process data behavior. Based on these double behavior characteristics, we introduce one-class classification to detect the corresponding anomalies, respectively. Besides, we also present the weighted mixed Kernel function and parameter optimization method to improve classification performance. Experimental results clearly demonstrate that the proposed approach has significant advantages of classification accuracy and detection efficiency.
语种英语
WOS标题词Science & Technology ; Technology
WOS类目Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
关键词[WOS]PRINCIPAL COMPONENT ANALYSIS ; INDUSTRIAL CONTROL-SYSTEM ; INTRUSION DETECTION ; SCADA SYSTEMS ; SUPPORT ; CHALLENGES ; AUTOMATION ; SECURITY ; KERNELS ; OCSVM
WOS研究方向Computer Science ; Engineering
引用统计
被引频次:4[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/21000
专题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Key Laboratory of Networked Control System, Chinese Academy of Sciences, Shenyang Institute of Automation, Shenyang 110016, China
推荐引用方式
GB/T 7714
Wan M,Shang WL,Zeng P. Double Behavior Characteristics for One-Class Classification Anomaly Detection in Networked Control Systems[J]. IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY,2017,12(12):3011-3023.
APA Wan M,Shang WL,&Zeng P.(2017).Double Behavior Characteristics for One-Class Classification Anomaly Detection in Networked Control Systems.IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY,12(12),3011-3023.
MLA Wan M,et al."Double Behavior Characteristics for One-Class Classification Anomaly Detection in Networked Control Systems".IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 12.12(2017):3011-3023.
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