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Learning from Routing Information for Detecting Routing Misbehavior in Ad Hoc Networks
Owing to ad hoc wireless networks’ properties, the implementation of complex security systems with higher computing resources seems troublesome in most situations. Therefore, the usage of anomaly or intrusion detection systems has attracted considerable attention. The detection systems are implement...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7663644/ https://www.ncbi.nlm.nih.gov/pubmed/33158143 http://dx.doi.org/10.3390/s20216275 |
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author | Basomingera, Robert Choi, Young-June |
author_facet | Basomingera, Robert Choi, Young-June |
author_sort | Basomingera, Robert |
collection | PubMed |
description | Owing to ad hoc wireless networks’ properties, the implementation of complex security systems with higher computing resources seems troublesome in most situations. Therefore, the usage of anomaly or intrusion detection systems has attracted considerable attention. The detection systems are implemented either as host-based, run by each node; or as cluster/network-based, run by cluster head. These two implementations exhibit benefits and drawbacks, such as when cluster-based is used alone, it faces maintaining protection when nodes delay to elect or replace a cluster head. Despite different heuristic approaches that have been proposed, there is still room for improvement. This work proposes a detection system that can run either as host- or as cluster-based to detect routing misbehavior attacks. The detection runs on a dataset built using the proposed routing-information-sharing algorithms. The detection system learns from shared routing information and uses supervised learning, when previous network status or an exploratory network is available, to train the model, or it uses unsupervised learning. The testbed is extended to evaluate the effects of mobility and network size. The simulation results show promising performance even against limiting factors. |
format | Online Article Text |
id | pubmed-7663644 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-76636442020-11-14 Learning from Routing Information for Detecting Routing Misbehavior in Ad Hoc Networks Basomingera, Robert Choi, Young-June Sensors (Basel) Article Owing to ad hoc wireless networks’ properties, the implementation of complex security systems with higher computing resources seems troublesome in most situations. Therefore, the usage of anomaly or intrusion detection systems has attracted considerable attention. The detection systems are implemented either as host-based, run by each node; or as cluster/network-based, run by cluster head. These two implementations exhibit benefits and drawbacks, such as when cluster-based is used alone, it faces maintaining protection when nodes delay to elect or replace a cluster head. Despite different heuristic approaches that have been proposed, there is still room for improvement. This work proposes a detection system that can run either as host- or as cluster-based to detect routing misbehavior attacks. The detection runs on a dataset built using the proposed routing-information-sharing algorithms. The detection system learns from shared routing information and uses supervised learning, when previous network status or an exploratory network is available, to train the model, or it uses unsupervised learning. The testbed is extended to evaluate the effects of mobility and network size. The simulation results show promising performance even against limiting factors. MDPI 2020-11-04 /pmc/articles/PMC7663644/ /pubmed/33158143 http://dx.doi.org/10.3390/s20216275 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Basomingera, Robert Choi, Young-June Learning from Routing Information for Detecting Routing Misbehavior in Ad Hoc Networks |
title | Learning from Routing Information for Detecting Routing Misbehavior in Ad Hoc Networks |
title_full | Learning from Routing Information for Detecting Routing Misbehavior in Ad Hoc Networks |
title_fullStr | Learning from Routing Information for Detecting Routing Misbehavior in Ad Hoc Networks |
title_full_unstemmed | Learning from Routing Information for Detecting Routing Misbehavior in Ad Hoc Networks |
title_short | Learning from Routing Information for Detecting Routing Misbehavior in Ad Hoc Networks |
title_sort | learning from routing information for detecting routing misbehavior in ad hoc networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7663644/ https://www.ncbi.nlm.nih.gov/pubmed/33158143 http://dx.doi.org/10.3390/s20216275 |
work_keys_str_mv | AT basomingerarobert learningfromroutinginformationfordetectingroutingmisbehaviorinadhocnetworks AT choiyoungjune learningfromroutinginformationfordetectingroutingmisbehaviorinadhocnetworks |