Honeypot game‐theoretical model for defending against APT attacks with limited resources in cyber‐physical systems

A cyber‐physical system (CPS) is a new mechanism controlled or monitored by computer algorithms that intertwine physical and software components. Advanced persistent threats (APTs) represent stealthy, powerful, and well‐funded attacks against CPSs; they integrate physical processes and have recently become an active research area. Existing offensive and defensive processes for APTs in CPSs are usually modeled by incomplete information game theory. However, honeypots, which are effective security vulnerability defense mechanisms, have not been widely adopted or modeled for defense against APT attacks in CPSs. In this study, a honeypot game‐theoretical model considering both low‐ and high‐interaction modes is used to investigate the offensive and defensive interactions, so that defensive strategies against APTs can be optimized. In this model, human analysis and honeypot allocation costs are introduced as limited resources. We prove the existence of Bayesian Nash equilibrium strategies and obtain the optimal defensive strategy under limited resources. Finally, numerical simulations demonstrate that the proposed method is effective in obtaining the optimal defensive effect.     

基于Stackelberg博弈的动态频谱接入控制

为了解决多主用户和多次级用户共存网络的频谱资源分配问题,提出了一种基于斯塔科尔伯格（Stackelberg）博弈的动态频谱接入控制算法。该算法通过三阶段Stackelberg博弈模拟主用户频谱竞价,博弈过程中次级用户以最大化传输速率为目的接入主用户频谱,同时设计了一种迭代过程来求解纳什均衡。实验计算与结果分析证明了纳什均衡唯一存在性的充要条件,并说明了迭代过程的收敛性以及主用户最佳效用的影响因素。     

基于单片机的嵌入式技术在3D视频游戏中的应用

近年来体感3D视频游戏风靡全球,此设计便是对体感3D视频游戏的一次探索和尝试。游戏由下位机和上位机两部分构成,下位机以C8051单片机为核心设计一个硬件电路,连接嵌入到鱼竿模型中的传感器中,负责采集并处理传感器信息。上位机以Virtools为开发工具,负责视频的输出控制。下位机根据上位机的请求通过串口向上位机传送控制信息,实现玩家通过真实的鱼竿在虚拟的屏幕中钓鱼的过程。     

“龙曦”网页游戏软件的开发

目前网页游戏已成为网络游戏的主流产品,而网页游戏所使用的开发技术也成为研究的热点。基于RIA平台设计的"龙曦"网页游戏软件,使用了当今流行的Flex开发技术。其游戏的动画使用Flash制作,通过ActionScript实现调用;画面层的管理,由ActionScript提供的功能来实现;消息数据以AMF格式封装,客户端与服务器的信息交互则采用线程通信技术。在对目前网页游戏常用开发技术进行综合比较的基础上,就"龙曦"网页游戏软件的开发进行了详细介绍。结果证明,使用Flex技术开发的网页游戏能够极大地提高用户体验。     

多冲突环境下的非合作三人对策集结模型

针对三人多冲突环境,建立了多个非合作三人对策的综合集结模型。根据多冲突环境下局中人受到的资源约束,得到局中人的可行策略串集合和多冲突环境下的综合结局空间,构建局中人在综合结局空间上的合成支付函数,进而建立多冲突环境下的非合作三人对策集结模型。实例说明了模型的实用性和有效性。     

多导弹协同攻击对策制导规律研究

针对多导弹协同攻击的作战要求,提出一种基于对策论的制导规律。将多枚导弹看作具有联合承诺的纯合作团队,建立了导弹-目标追逃对策模型,然后将每个时刻的策略选择问题转化为矩阵对策的形式,并运用排除法求出此矩阵对策的解,由此得到多枚导弹攻击目标的实时策略选择算法。仿真结果表明,该制导规律能够使各枚导弹以包围的态势攻击目标,为实际工程应用提供了参考。     

基于重叠联盟博弈的无人机侦察时间资源分配优化

在利用多无人机进行多目标侦察时,需要进行合理的任务分配。优化无人机资源与任务重要程度之间的关系,才能充分发挥多无人机侦察的优势。为了实现多无人机协同侦察时的时间资源分配优化,首先根据任务点和无人机的位置分布情况对多无人机进行预分配,然后对预分配后的空闲无人机进行协同时间资源优化。将空闲无人机协同时间资源分配问题建模为重叠联盟博弈模型,通过对所构建模型的求解,得出多无人机的协同侦察时间资源分配方案。仿真结果表明,优化时间资源后侦察系统的收益得到了提升。     

基于博弈模型的互联网低俗内容监管可行性研究

运用博弈工具分析我国互联网低俗内容监管,是为了从理论上真正搞清楚这样一个问题,即通过监管是否能够防止低俗内容在互联网上广泛传播。以博弈的视角对低俗内容的来源——内容提供商、平台服务提供商及以政府为主导的监管方的相关行为进行分析,在三者之间建立博弈模型,通过对其均衡解的分析揭示互联网内容监管的可行性。结论是肯定的,即互联网低俗内容监管机构与内容平台提供商之间能够实现(不检查,不违规)这一理想均衡状态,同时还可以采取措施避免另外两种均衡(不检查,违规)和(检查,违规)的出现。尽管我国互联网低俗内容监管的现状并不如此,但通过多样化的监管措施,防止互联网服务商违规是可实现的。     

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.     

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.