A Parallelism Technique to Improve Signature Based Intrusion Detection System
nowadays, it is vital for organization to protect their valuable information and internal resources from malicious access. Firewall is one of solution to prevent from unauthorized access, but it cannot monitor network traffic. To monitor and detect threats network monitoring tool like Intrusion Detection System (IDS) is required. Different IDS uses several techniques for Intrusion Detection. Signature based detection techniques are widely used in networks for fast response to detect threats. Because of the high-speed a large volume of data should be analysed and processed with high-speed infrastructure. It is time consuming process because signature based IDS scan all the network traffic and detect malicious packets. Snort is the best tool for signature based intrusion detection system can monitor the network traffic and generate alert for malicious packet. A parallel technique is a best alternative to reduce processing time and improve the performance of network intrusion detection system. In this paper, we have proposed data parallelism technique for signature based intrusion detection system using Snort in which detection rate is increased, the time to analyse packets and dropped packets are decreased. Our system is horizontally scalable that means we can increase or decrease hosts as per requirement.
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