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

Abstract

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.