基于云的虚拟网络的高效欺骗架构
An efficient deception architecture for cloud-based virtual networks
摘要：
新兴的欺骗性系统为基于云的虚拟网络中不断上升的安全问题提供了新的希望，特别是那些由中小型企业运营的虚拟网络。欺骗性系统的主要目标是在可访问Internet的基于云的虚拟网络中形成一层防御节点，以分散和欺骗恶意客户端。虽然许多方法提供了不同的模型，发展决策系统，痛苦有向图提出了一个有前途的决策模型分散强大的远程入侵。Misery有向图可以延迟对基于云的虚拟网络深处的目标的访问。痛苦有向图理论的一个核心挑战是验证它们在主要云计算平台中的适用性，以及测量适应它们的网络的效率。因此，需要可以通过长期支持技术实现的架构支持，并且可以部署用于大型网络。这项工作提出并分析了一个高吞吐量的痛苦有向图的架构，实施细节和性能分析。在Amazon Web Services中完全实现该架构会在请求处理中产生适度的性能延迟，同时高度延迟网络中的隐形入侵。
英文摘要：
Emerging deceptive systems present a new promise for the uprising security problems in cloud-based virtual networks, especially those operated by small and medium enterprises. The main goal of deceptive systems is to form a layer of defensive nodes in an Internet-accessible cloud-based virtual network to distract and deceive malicious clients. While numerous approaches provide distinct models for developing decisive systems, misery digraphs present a promising decisive model for distracting powerful remote intrusions. Misery digraphs can delay access to targets deep in a cloud-based virtual network. A central challenge to the theory of misery digraphs is verifying their applicability in prominent cloud computing platforms as well as measuring the efficiency of networks that adapt them. Thus, architectural support is needed that can be realized with long-term support technologies and can be deployed for large networks. This work presents and analyzes a high-throughput architecture for misery digraphs, embarking on implementation details and performance analysis. Full implementation of the architecture in Amazon Web Services imposes modest performance delays in the request processing, while highly delaying stealth intrusions in the network.
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