Detecting Packet Dropping Attacks Using Emergent Self-Organizing Maps in Mobile Ad Hoc Networks
Detecting Packet Dropping Attacks Using Emergent Self-Organizing Maps in Mobile Ad Hoc Networks
复制标题
在移动自组织网络中使用紧急自组织映射检测丢包攻击
DOI：
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发表时间：
2006
期刊：
影响因子：
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通讯作者：
C. Douligeris
中科院分区：
文献类型：
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作者：
Aikaterini Mitrokotsa;Rosa Mavropodi;C. Douligeris
无线网络技术的发展和
移动计算硬件的最新进展取得了
有可能在移动自组织网络中引入各种应用。不仅这些网络的基础设施本身就很脆弱，而且它们也增加了对其安全的要求。由于入侵防御机制，如加密和身份验证，在安全方面是不够的，我们需要第二道防线，入侵检测。本文重点研究异常检测技术，以发挥其能够检测未知攻击的主要优势。首先简要介绍了入侵检测系统，然后提出了一种适用于移动自组网的分布式方案。该异常检测机制基于神经网络，并使用从MAC层选择的特征来评估分组丢弃攻击。在不同的业务条件和移动模式下，对所提出的体系结构的性能进行了评估。
The evolution of wireless network technologies and
the recent advances in mobile computing hardware have made
possible the introduction of various applications in mobile ad hoc networks. Not only is the infrastructure of these networks inherently vulnerable but they have increased requirements regarding their security as well. As intrusion prevention mechanisms, such as encryption and authentication, are not sufficient regarding security, we need a second line of defense, Intrusion Detection. The focus of this paper is on anomaly detection techniques in order to exploit their main advantage of being able to detect unknown attacks. First, we briefly describe intrusion detection systems and then we suggest a distributed schema applicable to mobile ad hoc networks. This anomaly detection mechanism is based on a neural network and is evaluated for packet dropping attacks using features selected from the MAC layer. The performance of the proposed architecture is evaluated under different traffic conditions and mobility patterns.