International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE)
Many researchers have argued that Artificial Neural Networks (ANNs) can improve the performance of Intrusion Detection Systems (IDS). one of the central areas in network intrusion detection is how to build effective systems that are able to distinguish normal from intrusive traffic. In this paper, four different algorithms are used namely as multilayer perception, radial base function, logistic regression and voted perception. All these neural based algorithms are implemented in WEKA data mining tool to evaluate the performance.