Research Article
Detection of Cyber Attacks using Machine Learning based Intrusion Detection System for IoT Based Smart Cities
@ARTICLE{10.4108/eetsc.3222, author={Maria Nawaz Chohan and Usman Haider and Muhammad Yaseen Ayub and Hina Shoukat and Tarandeep Kaur Bhatia and Muhammad Furqan Ul Hassan }, title={Detection of Cyber Attacks using Machine Learning based Intrusion Detection System for IoT Based Smart Cities}, journal={EAI Endorsed Transactions on Smart Cities}, volume={7}, number={2}, publisher={EAI}, journal_a={SC}, year={2023}, month={6}, keywords={Internet of Things (IoT), Smart Cities, UAVs}, doi={10.4108/eetsc.3222} }- Maria Nawaz Chohan
Usman Haider
Muhammad Yaseen Ayub
Hina Shoukat
Tarandeep Kaur Bhatia
Muhammad Furqan Ul Hassan
Year: 2023
Detection of Cyber Attacks using Machine Learning based Intrusion Detection System for IoT Based Smart Cities
SC
EAI
DOI: 10.4108/eetsc.3222
Abstract
The world’s dynamics is evolving with artificial intelligence (AI) and the results are smart products. A smart city has smart city is collection of smart innovations powered with AI and internet of things (IoTs). Along with the ease and comfort that the concept of a smart city pointed at, many security concerns are being raised that hinders the path of its flourishment. An Intrusion Detection System (IDS) monitors the whole network traffic and alerts in case of any anomaly. A Machine Learning-based IDS intelligently senses the network threats, takes decisions about data packet legibility and alarm the user. Researchers have deployed various ML techniques to IDS to improve the detection accuracy. This work presents a comparative analysis of various ML algorithms trained over UNSW-NB15 dataset. ADA Boost, Linear Support Vector Machine (LSVM), Auto Encoder Classifier, Quadratic Support Vector Machine (QSVM) and Multi-Layer Perceptron algorithms are being employed in the stimulation. ADA Boost showed an excellent accuracy of 98.3% in the results.
Copyright © 2023 Chohan et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
