PCA-SVM Enabled Intelligent Intrusion Detection System for Detection of DDoS and Botnet Attack in Social Web of Things

Mahyudin Ritonga, Malik Jawarneh, Karthikeyan Kaliyaperumal, Nandula Anuradha

2023

Abstract

The Social Internet of Things is growing more pervasive in our everyday lives. Computing at the edge that is shared among several users, also known as collaborative edge computing is a relatively new method that has arisen as a potential solution to the rising resource crisis caused by the Internet of Things. Collaborative edge computing allows for previously inaccessible resources like computers, data storage, and network connections to be made available to devices located in remote locations. Because of the edge network’s close proximity to the endpoints, sensitive information about the users of the network might be exposed. As a direct consequence of this, dangers to the integrity of edge networks, such as botnet attacks, denial of service attacks, unauthorised access, packet sniffing, and man-in-the-middle assaults, are becoming increasingly prevalent. In order to address these problems and enhance edge network security, we describe an approach for the detection of intrusions. This article includes a mechanism for the detection of DDoS and Botnet attacks in Social Web of Things environments. In the first step of the process, a feature selection is determined using the PCA method. SVM, XGBoost, and AdaBoost are three algorithms that are utilised for the classification of malware data.

Paper Citation

in Harvard Style

Ritonga M., Jawarneh M., Kaliyaperumal K. and Anuradha N. (2023). PCA-SVM Enabled Intelligent Intrusion Detection System for Detection of DDoS and Botnet Attack in Social Web of Things. In Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT; ISBN 978-989-758-661-3, SciTePress, pages 314-318. DOI: 10.5220/0012615300003739

in Bibtex Style

@conference{ai4iot23,
author={Mahyudin Ritonga and Malik Jawarneh and Karthikeyan Kaliyaperumal and Nandula Anuradha},
title={PCA-SVM Enabled Intelligent Intrusion Detection System for Detection of DDoS and Botnet Attack in Social Web of Things},
booktitle={Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT},
year={2023},
pages={314-318},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012615300003739},
isbn={978-989-758-661-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT
TI - PCA-SVM Enabled Intelligent Intrusion Detection System for Detection of DDoS and Botnet Attack in Social Web of Things
SN - 978-989-758-661-3
AU - Ritonga M.
AU - Jawarneh M.
AU - Kaliyaperumal K.
AU - Anuradha N.
PY - 2023
SP - 314
EP - 318
DO - 10.5220/0012615300003739
PB - SciTePress