基于激励机制的网络攻防演化博弈模型研究

随着网络信息系统的日益复杂化,网络的安全性和用户隐私性引起了人们的高度重视,寻找能够维护网络安全、分析和预判网络攻防形式的新技术尤为重要.由于演化博弈理论的特性与网络攻防的特性较为契合,因此,本文对网络环境进行了分析,构建网络攻防场景,并在惩罚机制的基础上引入激励机制,提出了基于激励机制的攻防演化博弈模型.通过给出群体不同的问题情境,利用复制动态方程对局中人的策略选取进行演化分析.另外,在第三方监管部门对局中人管理的基础上,分析不同攻击时长时攻击群体的演化规律,证明攻击具有时效性.通过激励机制对防御群体策略选取的影响以及引入防御投资回报,来进一步证明增加激励机制的可行性.根据实验验证表明,本文提出的攻防演化博弈模型在不同的问题情境下均可达到稳定状态并获得最优防御策略,从而有效减少防御方的损失,遏制攻击方的攻击行为.

Research on Evolutionary Game Model of Network Attack and Defense Based on Incentive Mechanism

With the increasing complexity of network information system,people attach great importance to network security and user privacy.It is especially important to find newtechnologies that can maintain network security,analyze and predict the form of network attack and defense.Because the characteristics of evolutionary game theory are similar to those of network attack and defense,this paper analyses the network environment,constructs the network attack and defense scenarios,and introduces incentive mechanism on the basis of punishment mechanism,and proposes an evolutionary game model of attack and defense based on incentive mechanism.By giving the different problem situations of the group,the replication dynamic equation is used to analyze the evolution of the strategy selection of the player.In addition,on the basis of the management of players in the third-party supervision department,the evolution lawof attack groups in different attack time is analyzed,which proves that the attack is time-sensitive.The feasibility of the incentive mechanism is further proved by the impact of incentive mechanisms on the selection of defense group strategies and the introduction of defense investment returns.According to the experimental verification,the attack and defense evolutionary game model proposed in this paper can achieve the steady state and obtain the optimal defense strategy under different problem situations,thus effectively reducing the loss of the defender and curbing the attack behavior of the attacker.