• search hit 4 of 15
Back to Result List

Architecture of an intelligent Intrusion Detection System for Smart Home

  • Increasing cyber-attacks on Internet of Things (IoT) environments are a growing problem of digitized households worldwide. The purpose of this study is to investigate how an intelligent Intrusion Detection System (iIDS) can provide more security in IoT networks with a novel architecture, combining multiple classical and machine learning approaches. By combining classical security analysis methods and modern concepts of artificial intelligence, we increase the quality of attack detection and can therefore conduct dedicated attack suppression. The architectural image of the iIDS consists of different layers, which in parts achieve self-sufficient results. The results of the different modules are calculated by means of statement variables and evaluation techniques adapted for the individual module elements and subsequently combined by limit value considerations. The architecture image combines approaches for the analysis and processing of IoT network traffic and evaluates it to an aggregated score. From this result it can be determined whether the analyzed data indicates device misuse or attempted break-ins into the network. This study answers the questions whether a connection between classical and modern concepts for monitoring and analyzing IoT network traffic can be implemented meaningfully within a reliable architecture of an iIDS.

Export metadata

Additional Services

Share in Twitter Search Google Scholar Statistics
Metadaten
Author:Julian Graf, Katrin Neubauer, Sebastian Fischer, Rudolf Hackenberg
DOI:https://doi.org/10.1109/PerComWorkshops48775.2020.9156168
ISBN:978-1-7281-4716-1
Parent Title (English):2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops): 2020, Austin, Texas, USA
Publisher:IEEE
Document Type:conference proceeding (article)
Language:English
Year of first Publication:2020
Release Date:2022/01/27
Tag:Detection System; Internet of Things; Intrusion; artificial intelligence; smart Home
First Page:1
Last Page:6
Institutes:Fakultät Informatik und Mathematik
Fakultät Informatik und Mathematik / Labor Informationssicherheit und Complience (ISC)
Begutachtungsstatus:peer-reviewed
research focus:Digitalisierung
Licence (German):Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG