当前数据采集与监控系统(supervisory control and data acquisition,SCADA)系统面临着巨大的安全威胁,对其风险状况进行监测和评估是一项有效的应对措施。为有效处理评估过程中存在的模糊性和随机性问题,将云模型理论引入SCADA系统安...当前数据采集与监控系统(supervisory control and data acquisition,SCADA)系统面临着巨大的安全威胁,对其风险状况进行监测和评估是一项有效的应对措施。为有效处理评估过程中存在的模糊性和随机性问题,将云模型理论引入SCADA系统安全风险评估中,提出了一种基于云模型和组合权重的安全风险评估模型。该模型从SCADA系统的资产、威胁、脆弱性、安全措施4方面构建安全风险评估指标体系,采用最小二乘法求出评估指标的最优组合权重,借助云发生器得到评估指标的云模型数字特征和SCADA系统的综合评估云,然后基于黄金分割率构建标准评估云,同时结合改进的云相似度计算方法得出最终评估结果,最后通过实验验证了模型的有效性和可行性。研究结果表明,该模型能够得到准确的评估结果,与模糊综合评价等方法相比,该评估方法具备更高的可信性,评价效果更好。该方法不仅有助识别SCADA系统的安全风险威胁,而且为其他领域的安全风险评估提供了一定的参考。展开更多
Ventilation system is significant in underground metal mine of alpine region.Reasonable evaluation of ventilation effectiveness will lead to a practical improvement for the maintenance and management of ventilation sy...Ventilation system is significant in underground metal mine of alpine region.Reasonable evaluation of ventilation effectiveness will lead to a practical improvement for the maintenance and management of ventilation system.However,it is difficult to make an effective evaluation of ventilation system due to the lack of classification criteria with respect to underground metal mine in alpine region.This paper proposes a novel evaluation method called the cloud model-clustering analysis(CMCA).Cloud model(CM)is utilized to process collected data of ventilation system,and they are converted into cloud descriptors by CM.Cloud similarity(CS)based Euclidean distance(ED)is proposed to make clustering analysis of assessed samples.Then the classification of assessed samples will be identified by clustering analysis results.A case study is developed based on CMCA.Evaluation results show that ventilation effectiveness can be well classified.Moreover,CM is used alone to make comparison of evaluation results obtained by CMCA.Then the availability and validity of CMCA is verified.Meanwhile,difference of CS based ED and classical ED is analyzed.Two new clustering analysis methods are introduced to make comparison with CMCA.Then the ability of proposed CMCA to meet evaluation requirements of ventilation system is verified.展开更多
文摘当前数据采集与监控系统(supervisory control and data acquisition,SCADA)系统面临着巨大的安全威胁,对其风险状况进行监测和评估是一项有效的应对措施。为有效处理评估过程中存在的模糊性和随机性问题,将云模型理论引入SCADA系统安全风险评估中,提出了一种基于云模型和组合权重的安全风险评估模型。该模型从SCADA系统的资产、威胁、脆弱性、安全措施4方面构建安全风险评估指标体系,采用最小二乘法求出评估指标的最优组合权重,借助云发生器得到评估指标的云模型数字特征和SCADA系统的综合评估云,然后基于黄金分割率构建标准评估云,同时结合改进的云相似度计算方法得出最终评估结果,最后通过实验验证了模型的有效性和可行性。研究结果表明,该模型能够得到准确的评估结果,与模糊综合评价等方法相比,该评估方法具备更高的可信性,评价效果更好。该方法不仅有助识别SCADA系统的安全风险威胁,而且为其他领域的安全风险评估提供了一定的参考。
基金Project(2018YFC0808404)supported by National Key Research and Development Program of China。
文摘Ventilation system is significant in underground metal mine of alpine region.Reasonable evaluation of ventilation effectiveness will lead to a practical improvement for the maintenance and management of ventilation system.However,it is difficult to make an effective evaluation of ventilation system due to the lack of classification criteria with respect to underground metal mine in alpine region.This paper proposes a novel evaluation method called the cloud model-clustering analysis(CMCA).Cloud model(CM)is utilized to process collected data of ventilation system,and they are converted into cloud descriptors by CM.Cloud similarity(CS)based Euclidean distance(ED)is proposed to make clustering analysis of assessed samples.Then the classification of assessed samples will be identified by clustering analysis results.A case study is developed based on CMCA.Evaluation results show that ventilation effectiveness can be well classified.Moreover,CM is used alone to make comparison of evaluation results obtained by CMCA.Then the availability and validity of CMCA is verified.Meanwhile,difference of CS based ED and classical ED is analyzed.Two new clustering analysis methods are introduced to make comparison with CMCA.Then the ability of proposed CMCA to meet evaluation requirements of ventilation system is verified.
