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网络化系统中的数据安全与控制算法研究
其他题名Data Security and Control of Networked Systems
庞中华
2011-05-27
学位类型工学博士
中文摘要随着计算机技术、网络通信技术和控制技术的迅速发展,网络化控制系统(NCS)已逐渐成为工业自动化系统的发展趋势,以实现分布式管理与控制。然而,由于共享网络(特别是因特网和无线网络)的开放性、交互性和分散性等特点,在NCS中传输的反馈和控制信号面临着网络安全攻击的问题。 本文针对工业NCS,主要考虑两类攻击:欺骗攻击和拒绝服务(DoS)攻击。为保证NCS在这两类攻击的作用下仍保持良好的控制性能,本文从网络通信和控制理论角度出发,提出了积极的预防、检测和响应措施。本文的主要工作和贡献有以下几点: 1. 为了实现数据在网络化系统中传输的保密性,以及对欺骗攻击的检测和响应,从网络通信的角度出发,综合运用DES算法、MD5算法和时间戳策略,提出了一种安全传输机制(STM)。然后,针对NCS中的欺骗攻击,基于STM设计了一种安全网络化控制系统(SNCS)。最后,为了测试SNCS的性能,建立了两个实验平台:基于因特网的直流电机控制系统和基于无线城域网的一级直线倒立摆控制系统。实验结果验证了STM和SNCS的有效性。 2. 为了补偿网络通信约束对NCS产生的不利影响,如随机网络时延、数据包乱序与丢失,提出了一种基于网络环路时延(RTTD)的递推网络化预测控制(RNPC)方法,并基于切换系统理论推导了RNPC闭环系统的稳定性条件。然后,在分析欺骗攻击对SNCS性能影响的基础上,从网络通信和控制理论的角度出发,基于STM和RNPC设计了一种安全网络化预测控制系统(SNPCS)。它可以实现网络传输数据的加密与欺骗攻击的检测,并补偿欺骗攻击和网络通信约束对NCS造成的不利影响。仿真和实验结果验证了RNPC和SNPCS的有效性。 3. 将RNPC推广至慢时变非线性NCS,提出了一种基于网络RTTD的通用递推网络化预测控制(GRNPC)方法。然后,根据DoS攻击对NCS影响程度的不同,将其分为弱攻击和强攻击。对于弱DoS攻击和网络通信约束共同引入的网络时延、数据包乱序与丢失,采用GRNPC方法进行补偿;对于针对控制器端和网络通信信道的强DoS攻击,采用基于GRNPC的多控制器切换(MCS)策略进行处理。实验结果验证了GRNPC和MCS的有效性。 4. 从功能和安全性两方面,对基于Web的NCS实验室(NCSLab)进行了改进和完善。在功能上,为了能够让用户完全基于Web设计较为复杂的控制系统,提出了一种基于Web的C-MEX S-函数编译和调用方案,使NCSLab具有了功能扩展能力。在安全性上,针对NCSLab各部件所处的网络环境不同,采取不同的安全措施,为NCSLab设计了一套安全防范体系。最后,根据实际工程项目开发的需要,为NCSLab扩展了若干功能模块,以便于用户基于Web快速地进行控制系统的设计与实现。
英文摘要With the rapid developments in computer, network communication and control technologies, the networked control systems (NCSs) have been a growing trend in industrial automation systems for the purposes of distributed management and control. However, due to the properties of a shared network, especially the Internet and wireless networks, such as opening-up, interactivity, and decentralization, the feedback and control signals transmitted in NCSs are confronted with such problems as network security attacks. For the industrial NCSs, two types of attacks, deception attacks and denial of service (DoS) attacks, are considered. To guarantee the desired control performance when suffering from these attacks, the active mechanisms of prevention, detection and response have been proposed from the viewpoint of network communication and control theories in this thesis. The main work and achievements can be summarized as follows: (1) To achieve the confidentiality of the data transmitted in networked systems as well as the detection and response of deception attacks, a secure transmission mechanism (STM) is presented from a network communication point of view, which integrates the Data Encryption Standard (DES) algorithm, Message Digest (MD5) algorithm, and timestamp strategy. Then, a secure networked control system (SNCS) is designed based on the STM for the deception attacks in NCSs. To validate the SNCS, two experimental platforms are built: a Internet-based DC motor control system and a single linear inverted pendulum control system based on wireless metropolitan area networks (WMAN). Experimental results illustrate the effectiveness of the STM and SNCS. (2) To compensate for the adverse effects brought by the network communication constraints, such as random network time delay, packet disorder and dropout, a recursive networked predictive control (RNPC) method is proposed based on network round-trip time delays (RTTD). The stability condition of the closed-loop system is also derived based on the switched system theory. Then, on the basis of the analysis of the effects of deception attacks on the SNCS's performance, a secure networked predictive control system (SNPCS) is designed based on the STM and RNPC from the viewpoint of network communication and control theory. The SNPCS can provide the data confidentiality service, the detection of deception attacks, and the compensation for the adverse effects caused by deception attacks and network communication c...
关键词网络化控制系统 欺骗攻击 安全传输机制 递推网络化预测控制 非线性系统 拒绝服务攻击 Web实验室 Networked Control Systems Deception Attacks Secure Transmission Mechanism Recursive Networked Predictive Control Nonlinear Systems Dos Attacks Web Laboratory
语种中文
文献类型学位论文
条目标识符http://ir.ia.ac.cn/handle/173211/6355
专题毕业生_博士学位论文
推荐引用方式
GB/T 7714
庞中华. 网络化系统中的数据安全与控制算法研究[D]. 中国科学院自动化研究所. 中国科学院研究生院,2011.
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CASIA_20081801462801(7255KB) 暂不开放CC BY-NC-SA
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