基于统计模型的manet拒绝服务攻击检测

M. Rmayti, Y. Begriche, R. Khatoun, L. Khoukhi, D. Gaïti
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引用次数: 7

摘要

众所周知,由于缺乏集中控制、动态拓扑和有限的物理安全性等特点,移动自组网(manet)容易受到各种攻击。拒绝服务攻击仍然是无线网络的一个严重威胁。这些攻击不仅消耗系统资源,而且将合法用户与网络隔离。灰洞攻击是一种恶意节点在路由发现过程中丢弃接收到的部分数据包的攻击。为了检测这种攻击,本文提出了一种基于两个贝叶斯分类模型:伯努利和多项式的新方法。利用NS2仿真器进行了多次试验。我们的过滤器证明,故意丢弃数据包可以通过低水平的错误警报完全检测到。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Denial of Service (DoS) attacks detection in MANETs through statistical models
Mobile ad-hoc networks (MANETs) are well known to be vulnerable to various attacks, due to features such as lack of centralized control, dynamic topology, and limited physical security. Denial of Service attacks still represent a serious threat for wireless networks. These attacks not only consume the system resources but also isolate legitimate users from the network. Grayhole attack is one of these attacks, which occurs when a malicious node drop some of received data packets during the route discovery process. To detect this attack, we propose in this paper a novel approach based on two Bayesian classification models: Bernoulli and Multinomial. Several tests have been performed using NS2 simulator. Our filters prove that intentionally dropping packets can be fully detected with a low-level of false alerts.
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