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Security Risk Assessment of Cyber Physical Power System Based on Rough Set and Gene Expression Programming
  • ISSN号:1001-1390
  • 期刊名称:《电测与仪表》
  • 时间:0
  • 分类:TM73[电气工程—电力系统及自动化]
  • 作者机构:Research Institute of Advanced Technology, Nanjing University of Post and Telecommunications, School of Computer Science and Technology, Nanjing University of Post and Telecommunications, State Grid Smart Grid Research Institute
  • 相关基金:support by National Natural Science Foundation of China(61202354,51507084);Nanjing University of Post and Telecommunications Science Foundation(NUPTSF)(NT214203)
中文摘要:

Risk assessment is essential for the safe and reliable operation of cyber physical power system. Traditional security risk assessment methods do not take integration of cyber system and physical system of power grid into account. In order to solve this problem, security risk assessment algorithm of cyber physical power system based on rough set and gene expression programming is proposed. Firstly, fast attribution reduction based on binary search algorithm is presented. Secondly, security risk assessment function for cyber physical power system is mined based on gene expression programming. Lastly, security risk levels of cyber physical power system are predicted and analyzed by the above function model. Experimental results show that security risk assessment function model based on the proposed algorithm has high efficiency of function mining, accuracy of security risk level prediction and strong practicality.

英文摘要:

Risk assessment is essential for the safe and reliable operation of cyber physical power system. Traditional security risk assessment methods do not take integration of cyber system and physical system of power grid into account. In order to solve this problem, security risk assessment algorithm of cyber physical power system based on rough set and gene expression programming is proposed. Firstly, fast attribution reduction based on binary search algorithm is presented. Secondly, security risk assessment function for cyber physical power system is mined based on gene expression programming. Lastly, security risk levels of cyber physical power system are predicted and analyzed by the above function model. Experimental results show that security risk assessment function model based on the proposed algorithm has high efficiency of function mining, accuracy of security risk level prediction and strong practicality. ? 2014 Chinese Association of Automation.

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期刊信息
  • 《电测与仪表》
  • 中国科技核心期刊
  • 主管单位:哈尔滨电工仪表研究所
  • 主办单位:哈尔滨电工仪表研究所
  • 主编:刘献成
  • 地址:哈尔滨市松北区创新路2000号
  • 邮编:150028
  • 邮箱:dcyb@vip.163.com
  • 电话:0451-86693434 86611021
  • 国际标准刊号:ISSN:1001-1390
  • 国内统一刊号:ISSN:23-1202/TH
  • 邮发代号:14-43
  • 获奖情况:
  • 中文核心期刊,中国科技论文统计用刊,中国期刊方阵“双效”期刊
  • 国内外数据库收录:
  • 美国剑桥科学文摘,英国科学文摘数据库,中国中国科技核心期刊,中国北大核心期刊(2004版),中国北大核心期刊(2008版),中国北大核心期刊(2011版),中国北大核心期刊(2014版),中国北大核心期刊(2000版)
  • 被引量:15546