正在加载图片...
第11卷第5期 智能系统学报 Vol.11 No.5 2016年10月 CAAI Transactions on Intelligent Systems 0ct.2016 D0I:10.11992/is.201509020 网络出版地址:htp:/nw.cnki.net/kcms/detail/23.1538.TP.20160824.0928.006.html SCADA安全因素神经元的云推理机 研究与仿真 熊柳,曹谢东,李杰1,杨力2,刘增良3 (1.西南石油大学电气信息学院,四川成都610500:2.西南石油大学计算机科学学院,四川成都610500:3.中国 人民解放军国防大学信息作战研究所,北京100091) 摘要:为了解决SCADA系统信息安全的问题,本文提出了一种基于因素神经网络的主动防御方法。将SCADA系 统信息安全的影响因素映射到因素空间坐标中,然后利用知识因素的因素神经元表示方法,通过云模型推理机实现 了语言值表示的模糊概念到定量数据的转换,并通过云模型多规则多条件发生器进行规则推理,最后根据得到的期 望值又可以转换为定性语言值,这样就实现了对未知恶意程序行为操作可能性的预测。本文着重于利用基于云模 型的多条件多规则发生器实现推理,通过MATLAB进行算法设计和仿真,为油气SCADA系统信息安全防御的解决 方法提供了一种思路。 关键词:SCADA信息安全:因素空间:因素神经元:云模型:MATLAB仿真 中图分类号:TP18文献标志码:A文章编号:1673-4785(2016)05-0688-08 中文引用格式:熊柳,曹谢东,李杰,等.SC4DA安全因素神经元的云推理机研究与仿真[J].智能系统学报,2016,11(5):688-695. 英文引用格式:XIONG Liu,CAO Xiedong,LI Jie,etal.Study and simulation of the SCADA security factors neuron's cloud infer- ence engine[J].CAAI transactions on intelligent systems,2016,11(5):688-695. Study and simulation of the SCADA security factors neuron's cloud inference engine XIONG Liu',CAO Xiedong',LI Jie',YANG Li2,LIU Zengliang' (1.School of Electrical Information Engineering,Southwest Petroleum University,Chengdu 610500,China;2.School of Computer Science,Southwest Petroleum University,Chengdu 610500,China;3.Institute of Information Operation,University of National De- fense,Beijing 100091,China) Abstract:Over recent years,with the amount of incidents involving industrial control information systems,the safe- ty of these system has been given increased importance across the Globe,and several technical measures have been implented to improve this.This paper proposed an active defense method based on a factor neural network in refer- ence to SCADA information security.The different aspects of SCADA information security were mapped to factor co- ordinates,and the factor neuron method for knowledge factors was then used to transform this from a fuzzy concept represented by language)to quantitative data through a cloud inference engine.Inference was then conducted through generated multi conditions and multi rules based on a cloud model,so that it could then be transformed into a qualitative language (e.g.'more likely'based on Ex)to be able to forecast the consequences of unknown mali- cious programs.This paper focus on using a generator with multiple conditions and rules based on a cloud model to achieve inference,thus providing an idea of the oil and gas SCADA information security's defense response using algorithmic design and MATLAB-based simulations. Keywords:SCADA information security;factor space;factor neuron;cloud model;MATLAB simulation SCADA(supervisory control and data acquistion, 数据采集与监视控制系统)工业控制系统广泛运用 于工业、能源、交通、水利以及市政等领域,主要用于 收稿日期:2015-09-17.网络出版日期:2016-08-24. 生产数据采集和控制生产设备的运行。一旦工业控 基金项目:国家自然科学基金项目(61175122):四川省科技支撑计划 制系统信息安全出现漏洞,将对工业生产运行和国 (2015GZ0345):四川省教育厅重点项目(15ZA0049). 通信作者:熊柳.E-mail:beartreel991@163.com. 家经济安全造成重大隐患。一方面传统的病毒、木第 11 卷第 5 期 智 能 系 统 学 报 Vol.11 №.5 2016 年 10 月 CAAI Transactions on Intelligent Systems Oct. 2016 DOI:10.11992 / tis.201509020 网络出版地址:http: / / www.cnki.net / kcms/ detail / 23.1538.TP.20160824.0928.006.html SCADA 安全因素神经元的云推理机 研究与仿真 熊柳1 ,曹谢东1 ,李杰1 ,杨力2 ,刘增良3 (1. 西南石油大学 电气信息学院,四川 成都 610500; 2. 西南石油大学 计算机科学学院,四川 成都 610500; 3. 中国 人民解放军国防大学 信息作战研究所,北京 100091) 摘 要:为了解决 SCADA 系统信息安全的问题,本文提出了一种基于因素神经网络的主动防御方法。 将 SCADA 系 统信息安全的影响因素映射到因素空间坐标中,然后利用知识因素的因素神经元表示方法,通过云模型推理机实现 了语言值表示的模糊概念到定量数据的转换,并通过云模型多规则多条件发生器进行规则推理,最后根据得到的期 望值又可以转换为定性语言值,这样就实现了对未知恶意程序行为操作可能性的预测。 本文着重于利用基于云模 型的多条件多规则发生器实现推理,通过 MATLAB 进行算法设计和仿真,为油气 SCADA 系统信息安全防御的解决 方法提供了一种思路。 关键词:SCADA 信息安全;因素空间;因素神经元;云模型:MATLAB 仿真 中图分类号:TP18 文献标志码:A 文章编号:1673⁃4785(2016)05⁃0688⁃08 中文引用格式:熊柳,曹谢东,李杰,等. SCADA 安全因素神经元的云推理机研究与仿真[J]. 智能系统学报, 2016, 11(5): 688⁃695. 英文引用格式:XIONG Liu, CAO Xiedong, LI Jie, et al. Study and simulation of the SCADA security factors neuron’s cloud infer⁃ ence engine[J]. CAAI transactions on intelligent systems, 2016,11(5):688⁃695. Study and simulation of the SCADA security factors neuron’ s cloud inference engine XIONG Liu 1 , CAO Xiedong 1 , LI Jie 1 , YANG Li 2 , LIU Zengliang 3 (1. School of Electrical Information Engineering, Southwest Petroleum University, Chengdu 610500, China; 2. School of Computer Science, Southwest Petroleum University, Chengdu 610500,China; 3.Institute of Information Operation, University of National De⁃ fense, Beijing 100091,China) Abstract:Over recent years, with the amount of incidents involving industrial control information systems, the safe⁃ ty of these system has been given increased importance across the Globe, and several technical measures have been implented to improve this. This paper proposed an active defense method based on a factor neural network in refer⁃ ence to SCADA information security. The different aspects of SCADA information security were mapped to factor co⁃ ordinates, and the factor neuron method for knowledge factors was then used to transform this from a fuzzy concept (represented by language) to quantitative data through a cloud inference engine. Inference was then conducted through generated multi conditions and multi rules based on a cloud model, so that it could then be transformed into a qualitative language (e.g. ‘more likely’ based on Ex) to be able to forecast the consequences of unknown mali⁃ cious programs. This paper focus on using a generator with multiple conditions and rules based on a cloud model to achieve inference, thus providing an idea of the oil and gas SCADA information security’s defense response using algorithmic design and MATLAB⁃based simulations. Keywords:SCADA information security; factor space; factor neuron; cloud model; MATLAB simulation 收稿日期:2015⁃09⁃17. 网络出版日期:2016⁃08⁃24. 基金项目:国家自然科学基金项目(61175122);四川省科技支撑计划 (2015GZ0345);四川省教育厅重点项目(15ZA0049). 通信作者:熊柳. E⁃mail:beartree1991@ 163.com. SCADA( supervisory control and data acquistion, 数据采集与监视控制系统)工业控制系统广泛运用 于工业、能源、交通、水利以及市政等领域,主要用于 生产数据采集和控制生产设备的运行。 一旦工业控 制系统信息安全出现漏洞,将对工业生产运行和国 家经济安全造成重大隐患。 一方面传统的病毒、木
向下翻页>>
©2008-现在 cucdc.com 高等教育资讯网 版权所有