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Intrusion detection in mobile adhoc networks.

机译:移动自组织网络中的入侵检测。

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摘要

In the last few years, the performance and use of wireless technologies has increased tremendously, opening up avenues for applying these in previously less explored areas. One such field concerns mobile ad hoc networks (MANETs) in which mobile nodes organize themselves in a network without the help of any predefined infrastructure. Securing MANETs is an important part of deploying and utilizing them, since they are often used in critical applications where data and communications integrity in important. Existing solutions for wireless networks can be used to obtain a certain level of such security. Nevertheless, these solutions may not always be sufficient, as ad-hoc networks have their own vulnerabilities that cannot be addressed by these solutions. To obtain an acceptable level of security in such a context, traditional security solutions should be coupled with an intrusion detection mechanism. We propose using a quantitative method to detect intrusion in MANETS with mobile nodes. Our method is a behavioral anomaly based system, which makes it dynamic, scalable, configurable and robust. Finally, we verify our method by running simulations with mobile nodes using Ad-hoc on-demand Distance Vector (AODV) routing. It is observed that the malicious node detection rate is very good, and the false positive detection rate is low.
机译:在过去的几年中,无线技术的性能和使用已大大提高,这为在以前较少探索的领域中应用这些技术开辟了道路。一个这样的领域涉及移动自组织网络(MANET),其中移动节点无需任何预定义的基础结构即可在网络中自行组织。保护MANET是部署和利用它们的重要组成部分,因为它们通常用于对数据和通信完整性至关重要的关键应用中。用于无线网络的现有解决方案可以用于获得某种程度的这种安全性。但是,这些解决方案可能并不总是足够的,因为自组织网络具有其自身的漏洞,无法通过这些解决方案解决。为了在这种情况下获得可接受的安全级别,传统的安全解决方案应与入侵检测机制结合使用。我们建议使用定量方法来检测具有移动节点的MANETS中的入侵。我们的方法是一个基于行为异常的系统,使其具有动态性,可伸缩性,可配置性和鲁棒性。最后,我们通过使用Ad-hoc按需距离矢量(AODV)路由对移动节点进行仿真来验证我们的方法。可以看出,恶意节点的检测率非常高,误报检测率很低。

著录项

  • 作者

    Kumar, Kavitha.;

  • 作者单位

    The University of Toledo.;

  • 授予单位 The University of Toledo.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 M.S.
  • 年度 2010
  • 页码 96 p.
  • 总页数 96
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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