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DDoS prevention using third party auditor in cloud computing

机译:在云计算中使用第三方审核员预防DDoS

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摘要

Distributed denial of service (DDoS) attack is one of the prominent risk factors for the development of cloud service. It is a very hard task for novice cloud users to identify the real source of DDoS attack because the attacker spoofs the Internet Protocol and Media Access Control addresses. To address this problem, we propose a third party auditor-based packet traceback approach. The method uses Weibull distribution for analyzing the source of the DDoS attack. The approach provides an efficient and fruitful solution because of its strong identification factor. The identification factor depends on the weaknesses left by the intruder. We analyze the traffic pattern to generate attack alert for different cloud users. The advantage of this approach is that it reduces the overhead on the cloud user. With the help of Weibull distribution, we can easily obtain the availability, reliability and median life of DDoS defense in the cloud environment. To demonstrate our approach, we implement an application based on Hadoop and MapReduce framework. We tested this application based on various parameters. Our method has shown the tremendous improvement over the other state of the art methods. The experimental results are included to show the effectiveness of the proposed method for DDoS attack prevention and mitigation.
机译:分布式拒绝服务(DDoS)攻击是开发云服务的主要风险因素之一。对于新手云用户来说,识别DDoS攻击的真正来源是一项艰巨的任务,因为攻击者欺骗了Internet协议和媒体访问控制地址。为了解决此问题,我们提出了一种基于第三方审核员的数据包回溯方法。该方法使用Weibull分布来分析DDoS攻击的来源。由于其强大的识别因素,该方法提供了有效且富有成果的解决方案。识别因素取决于入侵者留下的弱点。我们分析流量模式以针对不同的云用户生成攻击警报。这种方法的优点是它减少了云用户的开销。借助Weibull分布,我们可以轻松地在云环境中获得DDoS防御的可用性,可靠性和平均寿命。为了演示我们的方法,我们实现了一个基于Hadoop和MapReduce框架的应用程序。我们基于各种参数测试了此应用程序。我们的方法已经显示出相对于其他现有方法的巨大进步。实验结果包括在内,以表明所提出的方法对DDoS攻击预防和缓解的有效性。

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