Markov game modeling of mimic defense and defense strategy determination

Network mimic defense technology enhances the robustness of active defense through the redundancy,dynamic and diversity as well as the decision feedback mechanism.However,little work has been done for its security assessment and existing classic game models are not suitable for its dynamic characteristics and lack of universality.A Markov game model was proposed to analyze the transfer relationship between offensive and defensive status and the measurement method of safety and reliability of mimic defense,and calculated the offensive and defensive game equilibrium through non-linear programming algorithm to determine the best defensive strategy considering performance.Experiments give a comparison with the multi-target hiding technique and shows that the mimic defense has a higher defensive effect.Combining with the specific network case,the specific attack and defense path for the exploit of the system vulnerability is given and the effectiveness of the defense strategy algorithm is verified.     

基于攻防信号博弈模型的防御策略选取方法

当前基于博弈理论的防御策略选取方法大多采用完全信息或静态博弈模型,为更加符合网络攻防实际,从动态对抗和有限信息的视角对攻防行为进行研究。构建攻防信号博弈模型,对策略量化计算方法进行改进,并提出精炼贝叶斯均衡求解算法。在博弈均衡分析的基础上,设计了最优防御策略选取算法。通过实验验证了模型和算法的有效性,并在分析实验数据的基础上总结了攻防信号博弈的一般性规律,能够指导不同类型防御者的决策。     

基于动态博弈的目标分配方法研究

以博弈论为基础,防空火力单元与攻击飞机多次对抗为作战背景,建立了基于动态博弈的防空火力单元目标分配模型.利用双矩阵博弈纳什均衡求解与数学规划的关系,建立了求解纳什均衡的二次规划,利用混合粒子群算法进行求解.仿真结果表明:用博弈论研究防空火力单元与攻击飞机多次对抗过程中的目标分配问题时,符合实际作战过程,真实性好,应用价值较高.     

Optimal strategy selection method for moving target defense based on signaling game

To solve the problem of the optimal strategy selection for moving target defense,the defense strategy was defined formally,the defense principle from the perspective of attack surface shifting and exploration surface enlarging was taken into account.Then,network attack-defense behaviors were analyzed from the sight of dynamic confrontation and bounded information.According to the analysis of attack-defense game types and confrontation process,the moving target defense model based on signaling game was constructed.Meanwhile,the method to quantify strategies was improved and the solution of perfect Bayesian equilibrium was proposed.Furthermore,the optimal defense strategy selection algorithm was designed by the equilibrium analysis.Finally,the simulation demonstrates the effectiveness and feasibility of the proposed optimal strategy and selection method.     

基于多阶段攻防信号博弈的最优主动防御

从网络攻防对抗的实际场景出发,针对具有不完全信息约束的多阶段动态攻防过程,构建了多阶段攻防信号博弈模型.针对多阶段攻防过程中信号作用衰减的问题,提出信号衰减因子进行量化描述.在此基础上,设计了多阶段攻防博弈均衡的求解方法,并给出了最优主动防御策略选取算法.通过仿真实验验证了本文模型和方法的有效性,并且分析总结了多阶段攻防博弈的规律.     

Website defense strategy selection method based on attack-defense game and Monte Carlo simulation

Aiming at the selection of security defense strategy in network attack-defense,the dynamic change process of mutual influence between attack-defense strategy was studied.Based on the game process of both offense and defense,the attack-defense game model was constructed,the attack process of the attacker based on Monte Carlo simulation was simulated and the attacker’s best attack utility was obtained,so as to calculate the best defensive utility of the defender.In order to maximize the effectiveness of network security defense,the optimal defense strategy under limited resources was implemented.Simulation experiments verify the effectiveness of the proposed method and analyze the influence of different parameter settings on the selection of defense strategy.     

基于权重优化的WMN信道分配算法研究

针对无线Mesh网中信道分配的适应性欠缺的问题,提出了一种基于权重优化的信道分配算法。该算法引入损耗因子使每次节点博弈的权重自动更新,将传统的静态博弈变为动态博弈,通过非强占优先制排队模型求节点的优先级使得信道分配更加公平。仿真结果表明,该算法在吞吐量和传输延时方面有所优化,验证了信道分配的公平性。     

Improving replicator dynamic evolutionary game model for selecting optimal defense strategies

In terms of the existence of strategy dependency in the same game group,network attack-defense evolutionary game model based on the improved replicator dynamics was constricted by introducing the intensity coefficient,which completed the method of calculating replicator dynamic rate.The improved replicator dynamic equation was adopted to solve the evolutionary equilibrium for the situation that both attack and defense have two optional strategies.The stability of the equilibrium points was analyzed by the local stability analysis method of Jacobian matrix,and the optimal defense strategies were obtained under different conditions.The results show that the strategy dependency between the players in the same group has a certain influence on the evolution of the game,both the incentive and the inhibition.Finally,the accuracy and validity of the model and method are verified by the experimental simulation,which provides a new theoretical support for solving the information security problems in the real.     

基于随机演化博弈模型的网络防御策略选取方法

针对攻防博弈系统中存在攻防策略集和系统运行环境改变等各类随机干扰因素的问题,传统确定性博弈模型无法准确描述攻防博弈过程.利用非线性Itó随机微分方程构建随机演化博弈模型,用于分析攻防随机动态演化过程.通过求解,并根据随机微分方程稳定性判别定理对攻防双方的策略选取状态进行稳定性分析,设计出基于随机攻防演化博弈模型的安全防御策略选取算法.最后,通过仿真验证了不同强度的随机干扰对攻防决策演化速率的影响,且干扰强度越大,防御者更倾向于选择强防御策略,攻击者更倾向于选择强攻击策略.本文模型和方法能够用于网络攻击行为预测和安全防御决策.     

基于多组博弈的新型网络流量控制模型

该文研究了具有强分布式特征和分层结构的通信网络流量控制问题,借鉴多组博弈模型来研究新型的网络流量控制模型,构造了基于网络流量速率和时延为参数的流量效用函数,使之能适度地满足不同业务的用户流量QoS需求,利用多组博弈优化模型建立了基于Min-Max的公平的网络流量控制博弈模型。理论上证明了提出的网络流量控制模型的非劣纳什策略存在性。数值仿真验证了模型的正确性,仿真结果验证了用户流量在非劣纳什均衡点的效用值是帕累托占优的。     

Optimal strategy selection approach of moving target defense based on Markov time game

For the problem that the existed game model was challenging to model the dynamic continuous characteristics of network attack and defense confrontation effectively,a method based on Markov time game was proposed to select the optimal strategy for moving target defense.Based on the analysis of the attack and defense confrontation process of moving targets,the set of moving target attack and defense strategies was constructed.The dynamics of the single-stage moving target defense process was described by time game.The randomness of multi-stage moving target defense state transformation was described by Markov decision process.At the same time,by abstracting the use of resource vulnerability by attack-defense participants as the alternation of the control of the attack surface,the versatility of the game model was effectively guaranteed.On this basis,the existence of equilibrium was analyzed and proved,and the optimal strategy selection algorithm was designed.Finally,the practicality of the constructed model and the effectiveness of the algorithm are verified by an application example.     

基于攻防微分博弈的网络安全防御决策方法

为准确分析快速变化和连续对抗的网络攻防行为,借鉴传染病动力学理论,提出安全状态演化模型分析网络系统安全状态的变化过程.在此基础上,构建攻防微分博弈模型,设计鞍点策略的求解方法,并以此为依据给出最优防御策略选取算法,实现在动态连续攻防过程中的实时最优防御决策.通过仿真实验验证了模型和算法的有效性,并在分析实验数据的基础上提出了针对性的网络防御建议.     

Defense strategies selection based on attack-defense evolutionary game model

Due to that the current network security researches based on game theory mostly use the completely rationality assumption,which is not consistent with the facts.Under the bounded rationality constraint of network attack-defense,attack-defense evolutionary game model and a method to solve evolutionary stable equilibrium based on the non-cooperative evolutionary game theory was proposed.The optimal defense strategy selection algorithm was designed based on the analysis of the evolutionary stable strategy.The effectiveness of the model and method proposed is verified by simulation results,through which some evolution conclusions of offensive behavior on the premise of limited rationality were drawn.     

Research on active defense based on multi-stage cyber deception game

In view of the characteristic that attacker depended on the detected information to decide the next actions,the non-cooperative signal game theory was applied to analyze cyber attack and defense.The signal deception mechanism in the process of cyber attack and defense was considered deeply by constructing a multi-stage cyber deception game model,and the dynamic analysis and deduction of the multi-stage cyber attack and defense was realized by considering the attenuation of cyber deception signals.A solution for multi-stage cyber deception game equilibrium was improved based on analysis of cyber attack and defense,and an optimal algorithm for selecting cyber deception defense strategies was designed.The effectiveness of the model is verified by simulations.The rules of multi-stage cyber deception games are summarized based on the results,which can provide effective guidance for the research on cyber active defense.     

Defense decision-making method based on incomplete information stochastic game and Q-learning

Most of the existing stochastic games are based on the assumption of complete information,which are not consistent with the fact of network attack and defense.Aiming at this problem,the uncertainty of the attacker’s revenue was transformed to the uncertainty of the attacker type,and then a stochastic game model with incomplete information was constructed.The probability of network state transition is difficult to determine,which makes it impossible to determine the parameter needed to solve the equilibrium.Aiming at this problem,the Q-learning was introduced into stochastic game,which allowed defender to get the relevant parameter by learning in network attack and defense and to solve Bayesian Nash equilibrium.Based on the above,a defense decision algorithm that could learn online was designed.The simulation experiment proves the effectiveness of the proposed method.     

基于攻防博弈模型的网络安全测评和最优主动防御

文中对攻防博弈模型中的相关内容展开了分析,讨论了攻防博弈模型的网络安全测评要点,包括信息安全测评分析、主动防御系统分析、脆弱性测评分析、防御代价定量分析等,并对攻防博弈模型的最优主动防御要点进行了整理,旨在提高对攻防博弈模型应用价值的认知水平,提升网络安全测评与防御的效果。     

基于Markov演化博弈的网络防御策略选取方法

当前运用博弈理论的网络安全研究大多采用完全理性假设,本文针对现实社会中攻防双方的有限理性限制条件和攻防过程的动态变化特征,基于非合作演化博弈理论,从有限理性约束出发,将演化博弈模型与Markov决策相结合,构建多阶段Markov攻防演化博弈模型,实现对多阶段、多状态攻防对抗的动态分析推演;依据博弈的折扣总收益设计目标函数,提出多阶段博弈均衡的求解方法,给出最优防御策略选取算法.通过实验验证了模型和方法的有效性.     

基于博弈论的网络攻防行为建模与态势演化分析

网络安全本质在对抗。针对现有研究缺乏从博弈视角分析网络攻防行为与态势演化关系的问题,该文提出一种网络攻防博弈架构模型(NADGM),借鉴传染病动力学理论以不同安全状态网络节点密度定义网络攻防态势,分析网络节点安全状态转移路径;以网络勒索病毒攻防博弈为例,使用NetLogo多Agent仿真工具开展不同场景下攻防态势演化趋势对比实验,得出增强网络防御效能的结论。实验结果验证了模型方法的有效性和可行性。     

面向进程控制流劫持攻击的拟态防御方法

为了防御进程控制流劫持攻击,从漏洞利用的角度对攻击过程建立了威胁模型,提出了截断关键漏洞利用环节的"要塞"防御.在研究拟态防御原理的基础上提出了进程的拟态执行模型,并对该模型进行了分析与有效性证明,拟态执行能够有效截断控制流劫持的攻击实施过程;实现了拟态执行的原型系统MimicBox,并对MimicBox进行了有效性验...     

有限异构资源条件下的工业控制拟态调度算法

网络空间拟态防御技术是应对信息系统未知漏洞后门攻击的有效手段,其安全性与执行体的数量、异构化程度以及具体的裁决调度策略紧密相关。然而在工业控制领域,工业应用的生态资源相对封闭,可实现的异构执行体个数受限。针对上述问题,提出一种适用于有限异构资源约束条件下的工业控制拟态调度算法。算法通过引入执行体上线保护寄存器、周期清洗定时器等,能够根据运行环境自适应选择合适的执行体上线,可有效防范N-1模与N模攻击。实验结果表明,所提出的三余度工业控制拟态调度算法,可自适应根据环境特性选择合适的执行体上线,即使在高强度攻击环境下,依然能保持99.24%的高可用概率。