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第17卷 智能系统学报 ·978· +主观权重 of Things technologies,2013,3(12):71-73,75 0.175 +客观权重 0.150 +组合权重 [5] BIAN Nayun,WANG Xiaofeng,MAO Li.Network se- 0.125 curity situational assessment model based on improved 周0.100 AHP FCE[C]//2013 Sixth International Conference on 0.075 Advanced Computational Intelligence (ICACI).Hang- 0.050 zhou:IEEE.2013:200-205. 0.025 [6] MARKOVIC-PETROVIC J D,STOJANOVIC M D 0 3 57911131517192123 BOSTJANCIC RAKAS S V.A fuzzy AHP approach for 指标层指标 security risk assessment in SCADA networks[J].Ad- 图6不同赋权方法的结果对比 vances in electrical and computer engineering,2019, Fig.6 Comparison of the results of different weighting 193):69-74. methods [7] LI Meng,LI Wenjing,YU Peng,et al.Risk prediction of 5结束语 the SCADA communication network based on entropy- gray model[C]//2017 13th International Conference on 本文首先从资产、威胁、脆弱性等方面构建 Network and Service Management(CNSM).Tokyo. 出SCADA系统风险评估指标体系,接着通过组 EEE,2017:256-261. 合权重优化模型确定了指标权重,云模型相关理 [8]万书亭,万杰,张成杰.基于灰色理论和变权模糊综合 论构建出风险评估模型,并通过实验验证了该模 评判的风电机组性能评估[J.太阳能学报,2015,36(9): 型。本文将主客观权重相结合,克服了单一权重 2285-2291 的信息损失问题,引入云模型理论,比传统的隶 WAN Shuting,WAN Jie,ZHANG Chengjie.Compre- 属度函数、白化函数在处理不确定性问题上考虑 hensive evaluation of wind power unit performance eval- 更加全面客观,改进了云相似度计算方法,更准 uation based on grey theory and variable weight fuzzy mathematics[J].Acta energiae solaris sinica,2015,36(9). 确地反映了标准评估云与综合评估云之间的相似 2285-2291 度,提高了评估结果的可靠性。本文的研究不仅 [9] YANG Li,CAO Xiedong,LI Jie.A new cyber security 有助于识别和预测SCADA系统的安全威胁,保 risk evaluation method for oil and gas SCADA based on 障SCADA系统的安全,而且对风险评估的进一 factor state space[J].Chaos,solitons fractals,2016,89: 步研究具有重要意义,但是文中的逆向云算法在 203-209. 样本量小的情况下,超熵估计值误差较大,因此, [10]YANG Li,CAO Xiedong,GENG Xinyu.A novel intelli- 今后的研究工作会对逆向云算法进行改进,提高 gent assessment method for SCADA information security 评价结果的精度。 risk based on causality analysis[J].Cluster computing, 2019,22(3):5491-5503. 参考文献: [11]李德毅,杜鹊.不确定性人工智能M.北京:国防工业 [I]王华忠.监控与数据采集(SCADA)系统及其应用M, 出版社,2005 北京:电子工业出版社,2010. [12]陈圆超,戴剑勇,谢东.矿井通风系统的组合赋权云模 [2] 陶耀东,李宁,曾广圣.工业控制系统安全综述仞计算 型综合评价.系统工程,2020,38(6):35-42 机工程与应用,2016,52(13):8-18 CHEN Yuanchao,DAI Jianyong,XIE Dong.Compre- TAO Yaodong,LI Ning,ZENG Guangsheng.Review of hensive evaluation of mine ventilation system based on industrial control systems security[J].Computer engineer- combination weighting cloud model[J].Systems engin- ing and applications,2016,52(13):8-18. eering,2020,38(6):35-42. [3] 王增光,卢昱,陈立云.网络安全风险评估方法综述 [13]张仕斌,许春香.基于云模型的信任评估方法研究[) 飞航导弹,2018(4):62-66,73 计算机学报,2013,36(2):422-431 WANG Zengguang,LU Yu,CHEN Liyun.Review of cy- ZHANG Shibin,XU Chunxiang.Study on the trust evalu- ber security risk assessment method[J].Aerodynamic ation approach based on cloud model[J].Chinese journal missile journal,2018(4):62-66,73. of computers,.2013,36(2):422-431. [4]姜莹莹,曹谢东,白琳,等.基于层次分析法的SCADA [14]刘常昱,冯芒,戴晓军,等.基于云X信息的逆向云新算 系统安全评价).物联网技术,2013,3(12):71-73,75. 法).系统仿真学报,2004,16(112417-2420. JIANG Yingying,CAO Xiedong,BAI Lin,et al.Safety LIU Changyu,FENG Mang,DAI Xiaojun,et al.A new evaluation of SCADA system based on AHP[J].Internet algorithm of backward cloud[J].Acta simulata systemat-1 5 3 7 9 13 17 21 11 15 19 23 指标层指标 0 0.025 0.050 0.075 0.100 0.125 0.150 0.175 权重 主观权重 客观权重 组合权重 图 6 不同赋权方法的结果对比 Fig. 6 Comparison of the results of different weighting methods 5 结束语 本文首先从资产、威胁、脆弱性等方面构建 出 SCADA 系统风险评估指标体系,接着通过组 合权重优化模型确定了指标权重,云模型相关理 论构建出风险评估模型,并通过实验验证了该模 型。本文将主客观权重相结合,克服了单一权重 的信息损失问题,引入云模型理论,比传统的隶 属度函数、白化函数在处理不确定性问题上考虑 更加全面客观,改进了云相似度计算方法,更准 确地反映了标准评估云与综合评估云之间的相似 度,提高了评估结果的可靠性。本文的研究不仅 有助于识别和预测 SCADA 系统的安全威胁,保 障 SCADA 系统的安全,而且对风险评估的进一 步研究具有重要意义,但是文中的逆向云算法在 样本量小的情况下,超熵估计值误差较大,因此, 今后的研究工作会对逆向云算法进行改进,提高 评价结果的精度。 参考文献: 王华忠. 监控与数据采集 (SCADA) 系统及其应用 [M]. 北京: 电子工业出版社, 2010. [1] 陶耀东, 李宁, 曾广圣. 工业控制系统安全综述 [J]. 计算 机工程与应用, 2016, 52(13): 8–18. TAO Yaodong, LI Ning, ZENG Guangsheng. Review of industrial control systems security[J]. Computer engineer￾ing and applications, 2016, 52(13): 8–18. [2] 王增光, 卢昱, 陈立云. 网络安全风险评估方法综述 [J]. 飞航导弹, 2018(4): 62–66,73. WANG Zengguang, LU Yu, CHEN Liyun. Review of cy￾ber security risk assessment method[J]. Aerodynamic missile journal, 2018(4): 62–66,73. [3] 姜莹莹, 曹谢东, 白琳, 等. 基于层次分析法的 SCADA 系统安全评价 [J]. 物联网技术, 2013, 3(12): 71–73,75. JIANG Yingying, CAO Xiedong, BAI Lin, et al. Safety evaluation of SCADA system based on AHP[J]. Internet [4] of Things technologies, 2013, 3(12): 71–73,75. BIAN Nayun, WANG Xiaofeng, MAO Li. Network se￾curity situational assessment model based on improved AHP_FCE[C]//2013 Sixth International Conference on Advanced Computational Intelligence (ICACI). Hang￾zhou: IEEE, 2013: 200−205. [5] MARKOVIC-PETROVIC J D, STOJANOVIC M D, BOSTJANCIC RAKAS S V. A fuzzy AHP approach for security risk assessment in SCADA networks[J]. Ad￾vances in electrical and computer engineering, 2019, 19(3): 69–74. [6] LI Meng, LI Wenjing, YU Peng, et al. Risk prediction of the SCADA communication network based on entropy￾gray model[C]//2017 13th International Conference on Network and Service Management (CNSM). Tokyo. IEEE, 2017: 256−261. [7] 万书亭, 万杰, 张成杰. 基于灰色理论和变权模糊综合 评判的风电机组性能评估 [J]. 太阳能学报, 2015, 36(9): 2285–2291. WAN Shuting, WAN Jie, ZHANG Chengjie. Compre￾hensive evaluation of wind power unit performance eval￾uation based on grey theory and variable weight fuzzy mathematics[J]. Acta energiae solaris sinica, 2015, 36(9): 2285–2291. [8] YANG Li, CAO Xiedong, LI Jie. A new cyber security risk evaluation method for oil and gas SCADA based on factor state space[J]. Chaos, solitons & fractals, 2016, 89: 203–209. [9] YANG Li, CAO Xiedong, GENG Xinyu. A novel intelli￾gent assessment method for SCADA information security risk based on causality analysis[J]. Cluster computing, 2019, 22(3): 5491–5503. [10] 李德毅, 杜鹢. 不确定性人工智能 [M]. 北京: 国防工业 出版社, 2005. [11] 陈圆超, 戴剑勇, 谢东. 矿井通风系统的组合赋权云模 型综合评价 [J]. 系统工程, 2020, 38(6): 35–42. CHEN Yuanchao, DAI Jianyong, XIE Dong. Compre￾hensive evaluation of mine ventilation system based on combination weighting cloud model[J]. Systems engin￾eering, 2020, 38(6): 35–42. [12] 张仕斌, 许春香. 基于云模型的信任评估方法研究 [J]. 计算机学报, 2013, 36(2): 422–431. ZHANG Shibin, XU Chunxiang. Study on the trust evalu￾ation approach based on cloud model[J]. Chinese journal of computers, 2013, 36(2): 422–431. [13] 刘常昱, 冯芒, 戴晓军, 等. 基于云 X 信息的逆向云新算 法 [J]. 系统仿真学报, 2004, 16(11): 2417–2420. LIU Changyu, FENG Mang, DAI Xiaojun, et al. A new algorithm of backward cloud[J]. Acta simulata systemat- [14] 第 17 卷 智 能 系 统 学 报 ·978·
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