On the Use of PSOKMeans++ for Enhancing the Efficiency of Mining Intrusions
9 Pages Posted: 12 Jul 2019
Date Written: March 15, 2019
Unique of most important issues in computer network organization is intrusion, which is one of greatest prevalent threats to network security and safety. In latest years, infiltration detection has become an significant area of security for the network. When every class of attacks is considered as a separate issue, IDS gets good results. Many surveys show that continuous increase in network infiltration has registered and personal privacy has been stolen and has become an important place for attacks in recent years. Network interruptions are illegal activities on the computer network. Therefore an actual penetration detection system is required. In this letter, we use intrusion detection system which usages particle cluster optimization K-Means ++ (PSOKM ++) to detect kind of intrusion. This paper demonstrations contrast amongst an intrusion detection system by consuming PSOKM ++ algo in the intrusion detection system (IDS) and KDD-99 dataset using IGKM algo. Research displays that intrusion detection is more accurate than the IGKM algo using the PSOKM ++ algo.
Keywords: Intrusion Detection System, Data Mining, KDD Cupp 99, IGKM, IPSOGMM
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