Open AccessSecuring IoT Network against DDoS Attacks using Multi-agent IDS
Author(s) -
Bedine Kerim
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1898/1/012033
Subject(s) - c4.5 algorithm , denial of service attack , computer science , internet of things , intrusion detection system , feature selection , naive bayes classifier , computer security , random forest , network security , computer network , data mining , artificial intelligence , machine learning , the internet , support vector machine , world wide web
The crucial issue of Internet of Things (IoT) is vulnerable towards various kinds of security threats, especially on denial-of-service (DoS) attacks as IoT network consists of millions of devices attached to the network. There are plenty of intrusion detection systems (IDSs) available for IoT networks, however, the accuracy detection yet still a big problem. To address the problem, this paper proposes an ensemble IDS for IoT networks. The proposed IDS uses Multi-agent System (MAS) concept and ensemble the Information Gain feature selection algorithm with J48 classifier algorithm for the proposed IDS. Experimental results show the proposed MAS-J48-IDS provides the best accuracy performance of 99.8% for all selected features compared to IDSs that use Naïve Bayesian (NB) and Random Forest (RF) classifiers. Besides, the use of MAS contributes towards the load balancing among the nodes in the network itself.