A Novel Intrusion Detection Scheme Using Support Vector Machine Fuzzy Network for Mobile Ad Hoc Networks

Huike Li, Daquan Gu
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引用次数: 11

Abstract

With the rapid development of the networking technology, the ad hoc technology has kept advancing apace. But wireless ad hoc networks present more security problems than the conventional wired and wireless networks. Therefore, the ever-increasing researchers are focusing on intrusion detection, as a complementary mechanism to the regular intrusion prevention approaches, which is needed to secure the wireless ad hoc networks. However, how to improve the accuracy of the intrusion detection efficiently in wireless ad hoc networks is still a challenging problem. In this paper, we propose a new approach for intrusion detection, which uses a novel Support Vector Machine Fuzzy Network (SVMFN) to make the detection more suitable and accurate in various wireless ad hoc network environments. The experimental results show that the generalization performance and the accuracy of identification are improved significantly compared to that of the traditional methods, and adapt to engineering applications.
一种基于支持向量机模糊网络的移动自组网入侵检测方案
随着网络技术的飞速发展,自组网技术也在飞速发展。但是无线自组织网络比传统的有线和无线网络存在更多的安全问题。因此,入侵检测作为常规入侵防御方法的补充机制,成为无线自组织网络安全的研究热点。然而,如何有效地提高无线自组织网络中入侵检测的准确性仍然是一个具有挑战性的问题。本文提出了一种新的入侵检测方法,该方法采用一种新颖的支持向量机模糊网络(SVMFN),使检测在各种无线自组织网络环境下更加适合和准确。实验结果表明,与传统方法相比,该方法的泛化性能和识别精度均有显著提高,适应工程应用。
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