从攻击者的角度探讨信息物理系统(Cyber-physical system,CPS)中隐蔽虚假数据注入(False data injection,FDI)攻击的最优策略.选取Kullback-Leibler(K-L)散度作为攻击隐蔽性的评价指标,设计攻击信号使得攻击保持隐蔽且最大程度地降低CP...从攻击者的角度探讨信息物理系统(Cyber-physical system,CPS)中隐蔽虚假数据注入(False data injection,FDI)攻击的最优策略.选取Kullback-Leibler(K-L)散度作为攻击隐蔽性的评价指标,设计攻击信号使得攻击保持隐蔽且最大程度地降低CPS远程状态估计的性能.首先,利用残差的统计特征计算远程状态估计误差协方差,将FDI最优策略问题转化为二次约束优化问题.其次,在攻击隐蔽性的约束下,运用拉格朗日乘子法及半正定规划推导出最优策略.最后,通过仿真实验验证所提方法与现有方法相比在隐蔽性方面具有显著优势.展开更多
This paper investigates the security issue of multisensor remote estimation systems.An optimal stealthy false data injection(FDI)attack scheme based on historical and current residuals,which only tampers with the meas...This paper investigates the security issue of multisensor remote estimation systems.An optimal stealthy false data injection(FDI)attack scheme based on historical and current residuals,which only tampers with the measurement residuals of partial sensors due to limited attack resources,is proposed to maximally degrade system estimation performance.The attack stealthiness condition is given,and then the estimation error covariance in compromised state is derived to quantify the system performance under attack.The optimal attack strategy is obtained by solving several convex optimization problems which maximize the trace of the compromised estimation error covariance subject to the stealthiness condition.Moreover,due to the constraint of attack resources,the selection principle of the attacked sensor is provided to determine which sensor is attacked so as to hold the most impact on system performance.Finally,simulation results are presented to verify the theoretical analysis.展开更多
Networked Control Systems (NCSs) have been implemented in several different industries. The integration with advanced communication networks and computing techniques allows for the enhancement of efficiency of industr...Networked Control Systems (NCSs) have been implemented in several different industries. The integration with advanced communication networks and computing techniques allows for the enhancement of efficiency of industrial control systems. Despite all the advantages that NCSs bring to industry, they remain at risk to a spectrum of physical and cyber-attacks. In this paper, we elaborate on security vulnerabilities of NCSs, and examine how these vulnerabilities may be exploited when attacks occur. A general model of NCS designed with three different controllers, i.e., proportional-integral-derivative (PID) controllers, Model Predictive control (MPC) and Emotional Learning Controller (ELC) are studied. Then three different types of attacks are applied to evaluate the system performance. For the case study, a networked pacemaker system using the Zeeman nonlinear heart model (ZHM) as the plant combined with the above-mentioned controllers to test the system performance when under attacks. The results show that with Emotional Learning Controller (ELC), the pacemaker is able to track the ECG signal with high fidelity even under different attack scenarios.展开更多
工业控制系统(Industrial Control System,ICS)的安全保障能力与其关乎国计民生的重要地位,具有极不协调的反差。为了揭示ICS潜在的攻击结构和方法,使得ICS防御策略研究更具实用性和针对性,将虚假数据注入(False Data Injection,FDI)攻...工业控制系统(Industrial Control System,ICS)的安全保障能力与其关乎国计民生的重要地位,具有极不协调的反差。为了揭示ICS潜在的攻击结构和方法,使得ICS防御策略研究更具实用性和针对性,将虚假数据注入(False Data Injection,FDI)攻击研究面向ICS,建立一种隐蔽的FDI攻击模型,可以在不影响ICS正常通信情况下注入虚假数据篡改监控变量。遵循该攻击模型,在煤制甲醇仿真工厂进行了验证实验,证明威胁切实存在,且难以察觉;同时,分析了威胁的严重性并讨论了防御措施。展开更多
基于自适应网络的分布式参数估计近年来受到了日益广泛的关注。现有的分布式参数估计算法尽管在无攻击的安全网络中表现良好,但在遭受如虚假数据注入(false data injection, FDI)攻击的对抗网络中,由攻击者注入的虚假数据(也称恶意数据...基于自适应网络的分布式参数估计近年来受到了日益广泛的关注。现有的分布式参数估计算法尽管在无攻击的安全网络中表现良好,但在遭受如虚假数据注入(false data injection, FDI)攻击的对抗网络中,由攻击者注入的虚假数据(也称恶意数据)会随着节点间的通信和协作在网络中扩散,导致算法估计性能的恶化。若算法不能从攻击中快速恢复估计性能(即算法对攻击不具有弹性),则可能导致严重的后果。为此,简要介绍了弹性分布式参数估计算法所解决的基本问题及基本算法原理;从FDI攻击检测和弹性参数估计策略2个方面,系统地总结了近年来弹性分布式参数估计算法的研究进展,并分析了其在遭受FDI攻击的对抗网络中的性能;最后,探讨了现有弹性分布式参数估计算法的发展趋势和未来潜在的研究方向。展开更多
虚假数据注入(false data injection,FDI)攻击是对电力系统运行影响较为严重的一种攻击。目前已有对交直流混联电网的FDI攻击方法的研究,但仍缺乏对交直流混联电网攻击策略的优化研究。为此,文中提出了面向交直流混联电网的FDI攻击策略...虚假数据注入(false data injection,FDI)攻击是对电力系统运行影响较为严重的一种攻击。目前已有对交直流混联电网的FDI攻击方法的研究,但仍缺乏对交直流混联电网攻击策略的优化研究。为此,文中提出了面向交直流混联电网的FDI攻击策略优化方法。首先,建立以FDI攻击损失最大为目标的双层优化模型,上层模型以电力系统经济损失最大为目标对FDI攻击策略进行优化;下层模型以发电机出力调整量和切负荷量最小为目标计算FDI攻击下的最大经济损失,考虑交直流混联电网安全约束和换相失败风险。然后,采用遗传算法对优化模型进行求解,生成最优攻击策略。最后,以改进的IEEE 14节点系统为例验证了模型的有效性。仿真结果表明,优化后的攻击策略能够显著提高安全约束经济调度(security constrained economic dispatch,SCED)的运行成本。展开更多
Modern power grid is fast emerging as a complex cyber-physical power system(CPPS)integrating physical current-carrying components and processes with cyber-embedded computing,which faces increasing cy-berspace security...Modern power grid is fast emerging as a complex cyber-physical power system(CPPS)integrating physical current-carrying components and processes with cyber-embedded computing,which faces increasing cy-berspace security threats and risks.In this paper,the state(i.e.,voltage)offsets resulting from false data injection(FDI)attacks and the bus safety characterization are applied to quantify the attack consequences.The state offsets are obtained by the state estimation method,and the bus safety characterization considers the power net-work topology as well as the vulnerability and connection relationship of buses.Considering the indeterminacy of attacker’s resource consumption and reward,a zero-sum game-theoretical model from the defender’s perspective with incomplete information is explored for the optimal allocation of limited defensive resources.The attacker aims to falsify measurements without triggering threshold alarms to break through the protection,leading to load shedding,over-voltage or under-voltage.The defender attempts to ensure the estimation results to be as close to the actual states as possible,and guarantee the system’s safety and efficient defensive resource utilization.The proposed solution is extensively evaluated through simu-lations using the IEEE 33-bus test network and real-time digital simulator(RTDS)based testbed experiments of the IEEE 14-bus network.The results demonstrate the effec-tiveness of the proposed game-theoretical approach for optimal defensive resource allocation in CPPS when lim-ited resources are available when under FDI attacks.Index Terms—Optimal strategy,game theory,Nash equilibrium,CPPS,FDI attack.展开更多
研究了信息物理系统中假数据注入(False data injection,FDI)攻击信号的检测问题.在分布式融合框架下,首先将FDI攻击信号建模为信息物理系统模型中的未知输入,从而使得攻击信号的检测问题转化为对FDI攻击信号的实时估计问题.其次,在每...研究了信息物理系统中假数据注入(False data injection,FDI)攻击信号的检测问题.在分布式融合框架下,首先将FDI攻击信号建模为信息物理系统模型中的未知输入,从而使得攻击信号的检测问题转化为对FDI攻击信号的实时估计问题.其次,在每个传感器端设计基于自适应卡尔曼滤波的FDI攻击信号的局部估计器;在融合中心端引入补偿因子,设计分布式信息融合准则以导出攻击信号的融合估计器.特别地,当FDI攻击信号是时变情况时,融合过程中补偿因子的引入可以大大提高对攻击信号的估计精度.最后,通过两个仿真算例验证所提算法的有效性.展开更多
为使配电网在虚假数据注入(false data injection,FDI)攻击下仍旧可以获得最优的状态估计,提出了一种新的状态估计算法,提高了配电网抵御FDI攻击的状态估计精度。在相量测量单元(phasor measurement units,PMU)被攻击的情况下,即测量值...为使配电网在虚假数据注入(false data injection,FDI)攻击下仍旧可以获得最优的状态估计,提出了一种新的状态估计算法,提高了配电网抵御FDI攻击的状态估计精度。在相量测量单元(phasor measurement units,PMU)被攻击的情况下,即测量值被篡改,最优卡尔曼估计可以分解为局部状态估计的加权和。该方法在某种意义上不安全,基于局部估计,提出了一种基于凸优化的方法,以取代加权和方法,将局部估计结合成一个安全的状态估计。仿真结果表明:当所有PMU量测设备都是良好时,所提的估计器与卡尔曼估计器的估计结果一致。当PMU设备被攻击造成量测量异常时,提供一个充分条件,在这个条件下安全状态估计器是稳定的。展开更多
随着智能电网的快速发展,针对电力系统的网络攻击事件频发,虚假数据注入(False Data Injection,FDI)攻击成为配电系统最受关注的攻击之一。为了降低FDI攻击给配电系统带来的损失,提出一种针对FDI攻击的韧性提升策略,采用安装安全设备和...随着智能电网的快速发展,针对电力系统的网络攻击事件频发,虚假数据注入(False Data Injection,FDI)攻击成为配电系统最受关注的攻击之一。为了降低FDI攻击给配电系统带来的损失,提出一种针对FDI攻击的韧性提升策略,采用安装安全设备和增设移动储能系统(Mobile Energy Storage System,MESS)的方式,以最小化失负荷和防御成本为目标,提出一个计及抵御FDI攻击能力的多目标优化模型。该模型在满足投资成本限制的基础上,通过优化安全设备安装位置和MESS的移动路线来提升配电系统的韧性,保证供电的可靠性。另外,为了达到MESS的最佳充放电策略,建立了基于Fourier⁃Legendre级数展开的连续函数来模拟储能的能量状态(State of Energy,SOE),从而更真实地反映MESS运作状态。随后运用多目标进化捕食策略(Multiple Preys Based Evolutionary Predator and Prey Strategy,MPEPPS)以得到配电系统可靠性和经济性之间权衡的Pareto前沿。最后,通过IEEE 33节点测试系统验证所提方法在降低系统运行费用与减少系统失负荷的有效性和实用性。展开更多
文摘从攻击者的角度探讨信息物理系统(Cyber-physical system,CPS)中隐蔽虚假数据注入(False data injection,FDI)攻击的最优策略.选取Kullback-Leibler(K-L)散度作为攻击隐蔽性的评价指标,设计攻击信号使得攻击保持隐蔽且最大程度地降低CPS远程状态估计的性能.首先,利用残差的统计特征计算远程状态估计误差协方差,将FDI最优策略问题转化为二次约束优化问题.其次,在攻击隐蔽性的约束下,运用拉格朗日乘子法及半正定规划推导出最优策略.最后,通过仿真实验验证所提方法与现有方法相比在隐蔽性方面具有显著优势.
基金supported by the National Natural Science Foundation of China(61925303,62173034,62088101,U20B2073,62173002)the National Key Research and Development Program of China(2021YFB1714800)Beijing Natural Science Foundation(4222045)。
文摘This paper investigates the security issue of multisensor remote estimation systems.An optimal stealthy false data injection(FDI)attack scheme based on historical and current residuals,which only tampers with the measurement residuals of partial sensors due to limited attack resources,is proposed to maximally degrade system estimation performance.The attack stealthiness condition is given,and then the estimation error covariance in compromised state is derived to quantify the system performance under attack.The optimal attack strategy is obtained by solving several convex optimization problems which maximize the trace of the compromised estimation error covariance subject to the stealthiness condition.Moreover,due to the constraint of attack resources,the selection principle of the attacked sensor is provided to determine which sensor is attacked so as to hold the most impact on system performance.Finally,simulation results are presented to verify the theoretical analysis.
文摘Networked Control Systems (NCSs) have been implemented in several different industries. The integration with advanced communication networks and computing techniques allows for the enhancement of efficiency of industrial control systems. Despite all the advantages that NCSs bring to industry, they remain at risk to a spectrum of physical and cyber-attacks. In this paper, we elaborate on security vulnerabilities of NCSs, and examine how these vulnerabilities may be exploited when attacks occur. A general model of NCS designed with three different controllers, i.e., proportional-integral-derivative (PID) controllers, Model Predictive control (MPC) and Emotional Learning Controller (ELC) are studied. Then three different types of attacks are applied to evaluate the system performance. For the case study, a networked pacemaker system using the Zeeman nonlinear heart model (ZHM) as the plant combined with the above-mentioned controllers to test the system performance when under attacks. The results show that with Emotional Learning Controller (ELC), the pacemaker is able to track the ECG signal with high fidelity even under different attack scenarios.
文摘工业控制系统(Industrial Control System,ICS)的安全保障能力与其关乎国计民生的重要地位,具有极不协调的反差。为了揭示ICS潜在的攻击结构和方法,使得ICS防御策略研究更具实用性和针对性,将虚假数据注入(False Data Injection,FDI)攻击研究面向ICS,建立一种隐蔽的FDI攻击模型,可以在不影响ICS正常通信情况下注入虚假数据篡改监控变量。遵循该攻击模型,在煤制甲醇仿真工厂进行了验证实验,证明威胁切实存在,且难以察觉;同时,分析了威胁的严重性并讨论了防御措施。
文摘基于自适应网络的分布式参数估计近年来受到了日益广泛的关注。现有的分布式参数估计算法尽管在无攻击的安全网络中表现良好,但在遭受如虚假数据注入(false data injection, FDI)攻击的对抗网络中,由攻击者注入的虚假数据(也称恶意数据)会随着节点间的通信和协作在网络中扩散,导致算法估计性能的恶化。若算法不能从攻击中快速恢复估计性能(即算法对攻击不具有弹性),则可能导致严重的后果。为此,简要介绍了弹性分布式参数估计算法所解决的基本问题及基本算法原理;从FDI攻击检测和弹性参数估计策略2个方面,系统地总结了近年来弹性分布式参数估计算法的研究进展,并分析了其在遭受FDI攻击的对抗网络中的性能;最后,探讨了现有弹性分布式参数估计算法的发展趋势和未来潜在的研究方向。
基金supported by the National Key Research and Development Program of China(No.2023YFB 3107603)the“Pioneer”and“Leading Goose”R&D Program of Zhejiang(No.2022C01239)+2 种基金the Special Support Plan for Zhejiang Province High-level Talents(No.2022R52012)the National Natural Science Foundation of China(No.52177119)the Funda-mental Research Funds for the Central Universities(Zhejiang University NGICS Platform).
文摘Modern power grid is fast emerging as a complex cyber-physical power system(CPPS)integrating physical current-carrying components and processes with cyber-embedded computing,which faces increasing cy-berspace security threats and risks.In this paper,the state(i.e.,voltage)offsets resulting from false data injection(FDI)attacks and the bus safety characterization are applied to quantify the attack consequences.The state offsets are obtained by the state estimation method,and the bus safety characterization considers the power net-work topology as well as the vulnerability and connection relationship of buses.Considering the indeterminacy of attacker’s resource consumption and reward,a zero-sum game-theoretical model from the defender’s perspective with incomplete information is explored for the optimal allocation of limited defensive resources.The attacker aims to falsify measurements without triggering threshold alarms to break through the protection,leading to load shedding,over-voltage or under-voltage.The defender attempts to ensure the estimation results to be as close to the actual states as possible,and guarantee the system’s safety and efficient defensive resource utilization.The proposed solution is extensively evaluated through simu-lations using the IEEE 33-bus test network and real-time digital simulator(RTDS)based testbed experiments of the IEEE 14-bus network.The results demonstrate the effec-tiveness of the proposed game-theoretical approach for optimal defensive resource allocation in CPPS when lim-ited resources are available when under FDI attacks.Index Terms—Optimal strategy,game theory,Nash equilibrium,CPPS,FDI attack.
文摘研究了信息物理系统中假数据注入(False data injection,FDI)攻击信号的检测问题.在分布式融合框架下,首先将FDI攻击信号建模为信息物理系统模型中的未知输入,从而使得攻击信号的检测问题转化为对FDI攻击信号的实时估计问题.其次,在每个传感器端设计基于自适应卡尔曼滤波的FDI攻击信号的局部估计器;在融合中心端引入补偿因子,设计分布式信息融合准则以导出攻击信号的融合估计器.特别地,当FDI攻击信号是时变情况时,融合过程中补偿因子的引入可以大大提高对攻击信号的估计精度.最后,通过两个仿真算例验证所提算法的有效性.
文摘为使配电网在虚假数据注入(false data injection,FDI)攻击下仍旧可以获得最优的状态估计,提出了一种新的状态估计算法,提高了配电网抵御FDI攻击的状态估计精度。在相量测量单元(phasor measurement units,PMU)被攻击的情况下,即测量值被篡改,最优卡尔曼估计可以分解为局部状态估计的加权和。该方法在某种意义上不安全,基于局部估计,提出了一种基于凸优化的方法,以取代加权和方法,将局部估计结合成一个安全的状态估计。仿真结果表明:当所有PMU量测设备都是良好时,所提的估计器与卡尔曼估计器的估计结果一致。当PMU设备被攻击造成量测量异常时,提供一个充分条件,在这个条件下安全状态估计器是稳定的。
文摘随着智能电网的快速发展,针对电力系统的网络攻击事件频发,虚假数据注入(False Data Injection,FDI)攻击成为配电系统最受关注的攻击之一。为了降低FDI攻击给配电系统带来的损失,提出一种针对FDI攻击的韧性提升策略,采用安装安全设备和增设移动储能系统(Mobile Energy Storage System,MESS)的方式,以最小化失负荷和防御成本为目标,提出一个计及抵御FDI攻击能力的多目标优化模型。该模型在满足投资成本限制的基础上,通过优化安全设备安装位置和MESS的移动路线来提升配电系统的韧性,保证供电的可靠性。另外,为了达到MESS的最佳充放电策略,建立了基于Fourier⁃Legendre级数展开的连续函数来模拟储能的能量状态(State of Energy,SOE),从而更真实地反映MESS运作状态。随后运用多目标进化捕食策略(Multiple Preys Based Evolutionary Predator and Prey Strategy,MPEPPS)以得到配电系统可靠性和经济性之间权衡的Pareto前沿。最后,通过IEEE 33节点测试系统验证所提方法在降低系统运行费用与减少系统失负荷的有效性和实用性。
