electronics-12-01757.pdf (2.58 MB)
An intelligent intrusion detection system for 5G-enabled internet of vehicles
journal contribution
posted on 2023-06-10, 06:41 authored by Breno Sousa, Naercio Magaia, Sara SilvaThe deployment of 5G technology has drawn attention to different computer-based scenarios. It is useful in the context of Smart Cities, the Internet of Things (IoT), and Edge Computing, among other systems. With the high number of connected vehicles, providing network security solutions for the Internet of Vehicles (IoV) is not a trivial process due to its decentralized management structure and heterogeneous characteristics (e.g., connection time, and high-frequency changes in network topology due to high mobility, among others). Machine learning (ML) algorithms have the potential to extract patterns to cover security requirements better and to detect/classify malicious behavior in a network. Based on this, in this work we propose an Intrusion Detection System (IDS) for detecting Flooding attacks in vehicular scenarios. We also simulate 5G-enabled vehicular scenarios using the Network Simulator 3 (NS-3). We generate four datasets considering different numbers of nodes, attackers, and mobility patterns extracted from Simulation of Urban MObility (SUMO). Furthermore, our conducted tests show that the proposed IDS achieved an F1 score of 1.00 and 0.98 using decision trees and random forests, respectively, which means that it was able to properly classify the Flooding attack in the 5G vehicular environment considered.
History
Publication status
- Published
File Version
- Published version
Journal
ElectronicsISSN
2079-9292Publisher
MDPI AGExternal DOI
Issue
8Volume
12Department affiliated with
- Informatics Publications
Research groups affiliated with
- Foundations of Software Systems Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2023-04-12First Open Access (FOA) Date
2023-04-12First Compliant Deposit (FCD) Date
2023-04-04Usage metrics
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