A Survey on different Machine Learning algorithms that are compatible with CSE-CIC IDS 2018 Dataset

This paper mainly devotes on these machine learning models: Decision Trees, Naive Bayes, Gradient descent, support vector machine and Random Forest describing different potential threats represented with CSE-CIC-IDS2018 dataset. Multiclass classifications have been included to check which of the machine models will effectively identify and prevent intrusion into the network.

Authors

Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2024-11-05
DOI
https://doi.org/10.36948/ijfmr.2024.v06i06.29927
Citations
1
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
0.71
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Survey on different Machine Learning algorithms that are compatible with CSE-CIC IDS 2018 Dataset

S. Radhika, S. Ashwini, J Senthil Kumar
1 citations
International Journal For Multidisciplinary Research
Artificial Intelligence in Healthcare
0.71
article

A Survey on different Machine Learning algorithms that are compatible with CSE-CIC IDS 2018 Dataset

S. Radhika, S. Ashwini, J Senthil Kumar
article en
1 citations

Abstract

This paper mainly devotes on these machine learning models: Decision Trees, Naive Bayes, Gradient descent, support vector machine and Random Forest describing different potential threats represented with CSE-CIC-IDS2018 dataset. Multiclass classifications have been included to check which of the machine models will effectively identify and prevent intrusion into the network.

International Journal For Multidisciplinary ResearchVol. 6(6)
Life in Land
Openalex Percentile: Top 20%
Artificial Intelligence in Healthcare
0.71
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A Survey on different Machine Learning algorithms that are compatible with CSE-CIC IDS 2018 Dataset — S. Radhika, S. Ashwini, et al. · International Journal For Multidisciplinary Research (2024) | TGRS Research Map | TGRS