多vnic智能突变:阻止客户端DNS缓存攻击的移动目标防御

Zan Zhou, Changqiao Xu, Tengchao Ma, Xiaohui Kuang
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引用次数: 1

摘要

随着大量研究工作投入到在线云服务平台的服务器端DNS安全增强中,复杂的apt倾向于开发客户端DNS攻击,而防御者的资源和能力有限。协同DNS攻击是一种具有代表性的最新客户端攻击模式,通过伪造DNS响应来暗中破坏用户缓存。与现有的静态防御方法不同,本文提出了一种多vnic智能变异的移动目标防御方案,使防御者从繁重的工作中解脱出来,同时也能有效地挫败难以捉摸的客户端DNS攻击。创建多个虚拟网卡,并以突变方式切换。因此,攻击者不得不盲目地猜测实际的网卡,暴露的风险很高。首先,我们构建了一个动态博弈论模型来捕捉攻击者和防御者的主要特征。其次,提出了一种自适应最优防御策略的强化学习机制。与几种最先进的技术相比,实验结果也突出了我们的防御方法的安全性能。
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Multi-vNIC Intelligent Mutation: A Moving Target Defense to thwart Client-side DNS Cache Attack
As massive research efforts are poured into server-side DNS security enhancement in online cloud service platforms, sophisticated APTs tend to develop client-side DNS attacks, where defenders only have limited resources and abilities. The collaborative DNS attack is a representative newest client-side paradigm to stealthily undermine user cache by falsifying DNS responses. Different from existing static methods, in this paper, we propose a moving target defense solution named multi-vNIC intelligent mutation to free defenders from arduous work and thwart elusive client-side DNS attack in the meantime. Multiple virtual network interface cards are created and switched in a mutating manner. Thus attackers have to blindly guess the actual NIC with a high risk of exposure. Firstly, we construct a dynamic game-theoretic model to capture the main characteristics of both attacker and defender. Secondly, a reinforcement learning mechanism is developed to generate adaptive optimal defense strategy. Experiment results also highlight the security performance of our defense method compared to several state-of-the-art technologies.
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