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Cluster-based mechanisms in support vector machine to integrate and detect spoofing

机译:支持向量机中基于集群的机制来集成和检测欺骗

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Wireless spoofing attack is mainly masquerades the IP address and degrade the performance of the network. In Existing an approach to address the potential spoofing attacks employ cryptographic schemes and requires key dissemination, Protection, and maintenance mechanisms. Although the cryptographic authentication approaches are not always desirable because of their overhead requirements. In this paper, Discover the presence of spoofing attack based on network adapter. Based on support vector machine (SVM) to control and prevent the malicious attacks such as an access point (AP) and denial-of-service (DOS) attack quickly. In addition, we developed the cluster-based mechanisms to improve the accuracy of determining the position of multiple attacks using localization system. The techniques can test through two test beds using both an 802.11 (WiFi) network and an 802.15.4 (ZigBee) network in two real office buildings. Experimental results show that the proposed methods can achieve over 95 percent Hit Rate of discovering the number of attackers.
机译:无线欺骗攻击主要是伪装IP地址并降低网络性能。在现有的解决潜在欺骗攻击的方法中,采用了加密方案,并且需要密钥分发,保护和维护机制。尽管由于密码认证方法的开销需求,所以并不总是希望使用密码认证方法。在本文中,发现基于网络适配器的欺骗攻击的存在。基于支持向量机(SVM)来快速控制和阻止恶意攻击,例如访问点(AP)和拒绝服务(DOS)攻击。此外,我们开发了基于群集的机制,以提高使用本地化系统确定多重攻击的位置的准确性。该技术可以在两个真实的办公大楼中使用802.11(WiFi)网络和802.15.4(ZigBee)网络通过两个测试台进行测试。实验结果表明,所提出的方法在发现攻击者数量方面可以达到95%以上的命中率。

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