Optimization of Rules for Intrusion Detection System (Org-Ids)
A new algorithm is proposed for Rule generation phase of proposed IDS to configure the rules by implementing Ant Colony Optimization Technique with Association Rule Mining and it is proved that this proposed algorithm outperforms the other existing algorithms.
Abstract
Computer Networks are prone to be attacked by a number of network attacks. To protect an individual system or the entire network from the malicious behaviour, a high level security system is needed. Intrusion detection system (IDS) is a system which give such protection to the network from the intrusions like misuse, unauthorised access etc. Even though many forms of new attacks come into practice, providing the security for the system from the known attack is also a challenging task. The solution is a Signature based IDS which is a potential tool to identify the known attack, sending alert and protect the networks. So a novel signature based IDS(ORG-IDS) with four phases such as Feature Selection, Classification, Optimized Rule generation and Pattern matching is proposed. For any efficient signature based IDS, it should have the signature rules in less number but it should be effective in identifying attacks with good time and memory complexity. In this paper, a new algorithm is proposed for Rule generation phase of proposed IDS to configure the rules by implementing Ant Colony Optimization Technique with Association Rule Mining . The parameters like number of rules, running time and memory utilization are measured and proved that this proposed algorithm outperforms the other existing algorithms.