A Robust Comparison of the KDDCup99 and NSL-KDD IoT Network Intrusion Detection Datasets Through Various Machine Learning Algorithms

by   Suchet Sapre, et al.

In recent years, as intrusion attacks on IoT networks have grown exponentially, there is an immediate need for sophisticated intrusion detection systems (IDSs). A vast majority of current IDSs are data-driven, which means that one of the most important aspects of this area of research is the quality of the data acquired from IoT network traffic. Two of the most cited intrusion detection datasets are the KDDCup99 and the NSL-KDD. The main goal of our project was to conduct a robust comparison of both datasets by evaluating the performance of various Machine Learning (ML) classifiers trained on them with a larger set of classification metrics than previous researchers. From our research, we were able to conclude that the NSL-KDD dataset is of a higher quality than the KDDCup99 dataset as the classifiers trained on it were on average 20.18 KDDCup99 dataset exhibited a bias towards the redundancies within it, allowing them to achieve higher accuracies.


page 1

page 4

page 6


A Comparative Analysis of Machine Learning Algorithms for Intrusion Detection in Edge-Enabled IoT Networks

A significant increase in the number of interconnected devices and data ...

Bridging the gap to real-world for network intrusion detection systems with data-centric approach

Most research using machine learning (ML) for network intrusion detectio...

Machine Learning Based Intrusion Detection Systems for IoT Applications

Internet of Things (IoT) and its applications are the most popular resea...

Intrusion Detection with Machine Learning Using Open-Sourced Datasets

No significant research has been conducted so far on Intrusion detection...

EagerNet: Early Predictions of Neural Networks for Computationally Efficient Intrusion Detection

Fully Connected Neural Networks (FCNNs) have been the core of most state...

Towards the Development of Realistic Botnet Dataset in the Internet of Things for Network Forensic Analytics: Bot-IoT Dataset

The proliferation of IoT systems, has seen them targeted by malicious th...

Please sign up or login with your details

Forgot password? Click here to reset