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Real-time Support Vector Machine based Network Intrusion Detection system using Apache Storm

机译:基于Apache Storm的基于网络入侵检测系统的实时支持

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Network intrusion detection is critical component of network management for security, quality of service and other purposes. These systems allow early detection of network intrusion and malicious activities; based on this detection, appropriate actions can be applied to manage these attacks. Several network intrusion detection systems are proposed and evaluated and many of them are currently in use to provide better security. Currently, computer networks are generating high volume of data traffic which cannot be analyzed by most network intrusion detection systems. This situation requires new techniques that can handle huge volume of real time data traffic and it must maintain the high throughput. We have proposed to network intrusion system based on support vector machine in this work. We also propose to use Apache Storm framework; which is a real-time distributed stream processing framework. This network intrusion system is tested for KDD 99 network intrusion dataset.
机译:网络入侵检测是安全,服务质量和其他目的网络管理的关键组成部分。这些系统允许早期发现网络入侵和恶意活动;基于此检测,可以应用适当的操作来管理这些攻击。提出了几种网络入侵检测系统,并评估了许多网络,目前用于提供更好的安全性。目前,计算机网络正在产生大多数网络入侵检测系统无法分析的高量数据流量。这种情况需要新的技术可以处理大量的实时数据流量,并且必须保持高吞吐量。我们已经提出了基于这项工作的支持向量机的网络入侵系统。我们还建议使用Apache Storm框架;这是一个实时分布式流处理框架。该网络入侵系统是测试KDD 99网络入侵数据集的。

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