Optimizing network traffic by generating association rules using hybrid apriori-genetic algorithm

Abstract

Association rule mining is a technique of generating frequent item sets so that the analysis on the basis of these sets can be used for different application areas such as analysis of network traffic. Although the frequent sets generated using apriori algorithm provides less computational time and provides less frequent sets, but the technique that we are implemented here provides less computational time as compared as well generated less sets and provides less rules for the network traffics. These frequent sets are used for the analysis of traffic in the network so that the analysis of different spams or any unwanted issues can be detected easily.