An Intelligent DDoS Attack Detection System Using Packet Analysis and Support Vector Machine
An Intelligent DDoS Attack Detection System Using Packet Analysis and Support Vector Machine
复制标题
基于数据包分析和支持向量机的智能DDoS攻击检测系统
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
V. Klyuev
中科院分区：
文献类型：
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作者：
Keisuke Kato;V. Klyuev
如今，许多公司和/或政府需要一个安全的系统和/或一个准确的入侵检测系统(IDS)来保护他们的网络服务和用户的私人信息。在网络安全领域，开发一种准确的分布式拒绝服务攻击检测系统是一项具有挑战性的任务。DDoS攻击使用被黑客劫持的多个僵尸阻塞目标的网络服务，并向目标服务器发送大量数据包。许多公司和/或政府的服务器都是攻击的受害者。在这样的攻击中，检测黑客是极其困难的，因为它们只通过来自另一个网络的多个机器人发送命令，然后在命令执行后迅速离开机器人。提出的策略是利用网络报文分析技术检测DDoS攻击模式，并利用机器学习技术研究DDoS攻击模式，从而开发一个DDoS攻击智能检测系统。在这项研究中，我们分析了应用互联网数据分析中心提供的大量网络数据包，并使用径向基函数核的支持向量机实现了检测系统。该检测系统对DDoS攻击的检测准确无误。
Nowadays, many companies and/or governments require a secure system and/or an accurate intrusion detection system (IDS) to defend their network services and the user’s private information. In network security, developing an accurate detection system for distributed denial of service (DDoS) attacks is one of challenging tasks. DDoS attacks jam the network service of the target using multiple bots hijacked by crackers and send numerous packets to the target server. Servers of many companies and/or governments have been victims of the attacks. In such an attack, detecting the crackers is extremely difficult, because they only send a command by multiple bots from another network and then leave the bots quickly after command execute. The proposed strategy is to develop an intelligent detection system for DDoS attacks by detecting patterns of DDoS attack using network packet analysis and utilizing machine learning techniques to study the patterns of DDoS attacks. In this study, we analyzed large numbers of network packets provided by the Center for Applied Internet Data Analysis and implemented the detection system using a support vector machine with the radial basis function (Gaussian) kernel. The detection system is accurate in detecting DDoS attacks.