… The complexity of soft computing is greatly reduced if the numbers of features in a … , soft
computing fuzzy logic system is proposed to enhance network security through intrusion detection…

… Our future work will focus on reducing features for the classifiers by methods of feature
selection. Also, the work will be continued to study the fitness function of the genetic …

… Reducing the size of measures means that … In this paper, the measure size is reduced based
on the locality of user ac… As a result of mapping of the measures, we can reduce the data. …

… for intrusion detection via deep learning method presented in this document followed similar
thinking. We use the hierarchical exploration and RNN-based model for classification based …

… We also demonstrated the importance of feature reduction to model lightweight intrusion
detection systems. Finally, we propose a hybrid architecture involving ensemble and base …

… and reduced KDD Cup 99 datasets shows that identified reduced data performance is
better than featured dataset. Some other neural network-based approaches developed for IDS …

… et al.’s work, a potential function clustering method was used between the first and second
layer. This clustering algorithm significantly reduced the dimensions seen by neurons in the …

… Soft computing techniques are increasingly being … soft computing techniques for intrusion
detection. Due to increasing incidents of cyber attacks, building effective intrusion detection …

… work is to design and form the intelligent intrusion detection system (I-IDS) using the … turn
decrease the performance of the protocol applied to the deployed system of intrusion detection. …

… From additional network configuration details provided by intrusion detection administrator,
we can reduce ambiguous area. But this raises another challenge of dealing with multiple …