… the performance of deep learning algorithms in intrusion detection. A comparative analysis
… convolutional neural network, and long short-term memory using the CIC-IDS 2017 dataset. …

… Metric Performance IDS execution examination is assessed as far as the quantity of features
… of the machine learning algorithm. Several metrics have been designed to measure IDS …

… dataset with a focus on reporting the accuracy of an algorithm or method. The research to
date has been predominantly in optimizing the salgorithms used in ML, towards improving the …

… impact of issues present in the CIC-IDS 2017 and CIC-CSE-IDS 2018 datasets. We
evaluate the impact of labeling errors on standard ML/DL algorithms, since judgment of validity …

… that was trained using our CIC IDS-2017 data and compare the results across the different
attack vectors. Our goal was to use machine-learning algorithms to create a predictive model …

… We exploited different machine learning algorithms such as (Random Forest, GaussianNB,
… the literature that present innovative IDS with application on the CSE-CIC-IDS-2018 dataset, …

… how efficiently the results of an intrusion detection dataset can be generalized. For performance
evaluation, the authors used 12 supervised learning algorithms from different families: …

… In this paper we used the BPSO algorithm for its ability to deal with real optimization … as
CSE-CIC-IDS2018 data set. Deep neural networks with swarm intelligence algorithms showed …

… a model that adopts an effective algorithm for extracting features, so we use deep learning …
that use deep learning for intrusion detection in network NIDS are presented. Algorithms show …

… to survey deep learning based intrusion detection system … in deep learning algorithms or
in intrusion detection systems. … The CIC IDS 2017 dataset contains common attacks, which …