Jalali_Mosallam_Seyed_Pedrum.pdf (3.16 MB)
Download fileNetwork intrusion detection using machine learning
thesis
posted on 2021-05-22, 11:59 authored by Seyed Pedrum Jalali MosallamIn this research we have studied the use of machine learning techniques in detecting network
intrusions. Most research in the field has used the very outdated dataset (KDDCup99) which
consists of a set handcrafted features. In our research we present models that work well on both
the older dataset and on newer datasets such as ISCX2014 and ISCX2012. We also present
methods for extracting features from these datasets. Another issue we found with most research in
this field is that they do not study the effect of surges in regular network traffic and how that might
affect the model. We put our model to test in 10x traffic and show its effectiveness under these
conditions. We also study how semi-supervised models can be used in training NIDS models
without directly showing them labeled data.
History
Language
engDegree
- Master of Science
Program
- Computer Science
Granting Institution
Ryerson UniversityLAC Thesis Type
- Thesis