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A distributed intrusion detection system for resource-constrained devices in ad-hoc networks

机译:Ad-hoc网络中资源受限设备的分布式入侵检测系统

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摘要

This paper describes the design and implementation of a two-stage intrusion detection system (IDS) for use with mobile ad-hoc networks. Our anomaly-based intrusion detection is provided by analyzing the context from the application-level interactions of networked nodes; each interaction corresponds to a specific function or behavior within the operational scenario of the network. A static set of behaviors is determined offline, and these behaviors are tracked dynamically during the operation of the network. During the first stage of the IDS, our detection strategy employs the analysis of global and local maxima in the probability density functions of the behaviors to isolate deviance at the granularity of a single node. This stage is used to capture the typical behavior of the network. The first stage also provides tuning and calibration for the second stage. During the second stage, a cross-correlative component is used to detect multiple threats simultaneously. Our approach distributes the IDS among all connected network nodes, allowing each node to identify potential threats individually. The combined result can detect deviant nodes in a scalable manner and can operate in the presence of a density of deviant nodes approaching 22%. Computational requirements are reduced to adapt optimally to embedded devices on an ad-hoc network.
机译:本文介绍了用于移动自组织网络的两阶段入侵检测系统(IDS)的设计和实现。我们的基于异常的入侵检测是通过分析来自网络节点的应用程序级交互的上下文来提供的;每个交互都对应于网络操作场景中的特定功能或行为。脱机确定一组静态行为,并在网络运行期间动态跟踪这些行为。在IDS的第一阶段,我们的检测策略对行为的概率密度函数进行全局和局部最大值分析,以隔离单个节点粒度上的偏差。此阶段用于捕获网络的典型行为。第一阶段还为第二阶段提供调整和校准。在第二阶段,使用互相关组件同时检测多个威胁。我们的方法将IDS分布在所有连接的网络节点之间,从而允许每个节点分别识别潜在的威胁。组合的结果可以以可伸缩的方式检测偏差节点,并且可以在偏差节点的密度接近22%的情况下运行。降低了计算要求,以最佳地适应自组织网络上的嵌入式设备。

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