Using permutation importance the original 69 features in the dataset have been reduced to only 10 features, which allows the reduction of models execution time, and leads to faster intrusion detection systems. The reduced dataset was evaluated using Random Forest algorithm, and the obtained results ...
Information Gain, ranking and grouping the features according to the minimum weight values to select relevant and significant features, and then implements Random Forest (RF), Bayes Net (BN), Random Tree (RT), Naive Bayes (NB) and J48 classifier algorithms in experiments on CICIDS-2017 dataset...
incomplete attack coverage, anonymizedpacket information and payload which does not ref l ect the current real-ity, or they lack some feature set and metadata. This paper focused onCICIDS2017 as the last updated IDS dataset that contains benign andseven common attack network f l ...
This paper focused on CICIDS2017 as the last updated IDS dataset that contains benign and seven common attack network flows, which meets real world criteria and is publicly available. It also evaluates the effectiveness of a set of network traffic features and machine learning algorithms to ...
Evaluation of Network Intrusion Detection with Features Selection and Machine Learning Algorithms on CICIDS-2017 DatasetOneRREPTreeWEKACICIDS-2017 Data SetFeature Selection AlgorithmsIn the era of network Security, the Intrusion Detection System (IDS) plays an important role in information security. As ...
To evaluate the effectiveness of the IDS Canadian Institute of Cybersecurity presented a state of art dataset named CICIDS2017, consisting of latest threats and features. The dataset draws attention of many researchers as it represents threats which were not addressed by the older datasets. While ...
We show that the random forest algo-rithm as one of our best performing algorithm can achieve better resultswith superfeatures versus top selected features.Keywords: Intrusion detection · IDS dataset · DoS · Web attack ·Inf i ltration · Brute force · Superfeature1 IntroductionIntrusion ...
1presents 7 parameters. The first one is year of creation of each dataset. Then the number of features gives us the quantity of input data and labels characterizing each record. The number of records and the distribution between normal traffic and data are important information for dataset ...
CICIDS-2017 data set overcome above major flaws [ 1 ]. Consequently, this paper assesses the performance of CICIDS-2017 data set by applying various machine learning algorithms such as Convolution Neural Network (CNN), Naive Bayes (NB) and Random Forest (RF), RF with highly ranked features, ...
Having prior knowledge of the dataset structure and statistical behavior of various features will help in implementing the suitable algorithms to obtain maximum detection rates with minimum computational time. To fulfil this task and to achieve the above-mentioned contributions, the experiments are ...