Riecker, Michael ; Almon, Lars ; Hollick, Matthias (2017)
Lightweight Detection of Denial-of-Service Attacks on Wireless Sensor Networks Revisited.
2017 IEEE 42nd Conference on Local Computer Networks (LCN). Singapore (09.10.2017-12.10.2017)
doi: 10.1109/LCN.2017.110
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
The resource-constrained nature of sensor nodes makes wireless sensor networks (WSNs) especially susceptible to denial-of-service (DoS) attacks. Due to the wireless communication medium, it is difficult to prevent attacks such as jamming. Hence, mechanisms to detect attacks during operation are required. The current generation of intrusion detection systems are still rather heavyweight, as some form of collaboration is typically needed. In this paper, we study the behavior of a large number of node-centric metrics under jamming and blackhole attacks, by applying a logistic regression. In our experiments, we vary several parameters, such as traffic intensity, transmission power, and attacker location. We consider the most common topologies in wireless sensor networks such as central data collection and meshed multi-hop networks by using the collection tree and the mesh protocol. The created regression models are then used to implement a fully localized intrusion detection system requiring no collaboration, showing that certain models can be generalized to different networks.
Typ des Eintrags: | Konferenzveröffentlichung |
---|---|
Erschienen: | 2017 |
Autor(en): | Riecker, Michael ; Almon, Lars ; Hollick, Matthias |
Art des Eintrags: | Bibliographie |
Titel: | Lightweight Detection of Denial-of-Service Attacks on Wireless Sensor Networks Revisited |
Sprache: | Englisch |
Publikationsjahr: | 2017 |
Verlag: | IEEE |
Veranstaltungstitel: | 2017 IEEE 42nd Conference on Local Computer Networks (LCN) |
Veranstaltungsort: | Singapore |
Veranstaltungsdatum: | 09.10.2017-12.10.2017 |
DOI: | 10.1109/LCN.2017.110 |
URL / URN: | https://ieeexplore.ieee.org/document/8109386 |
Kurzbeschreibung (Abstract): | The resource-constrained nature of sensor nodes makes wireless sensor networks (WSNs) especially susceptible to denial-of-service (DoS) attacks. Due to the wireless communication medium, it is difficult to prevent attacks such as jamming. Hence, mechanisms to detect attacks during operation are required. The current generation of intrusion detection systems are still rather heavyweight, as some form of collaboration is typically needed. In this paper, we study the behavior of a large number of node-centric metrics under jamming and blackhole attacks, by applying a logistic regression. In our experiments, we vary several parameters, such as traffic intensity, transmission power, and attacker location. We consider the most common topologies in wireless sensor networks such as central data collection and meshed multi-hop networks by using the collection tree and the mesh protocol. The created regression models are then used to implement a fully localized intrusion detection system requiring no collaboration, showing that certain models can be generalized to different networks. |
Freie Schlagworte: | Wireless Sensor Networks; Denial-of-Service; Intrusion Detection |
Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Sichere Mobile Netze LOEWE LOEWE > LOEWE-Schwerpunkte LOEWE > LOEWE-Schwerpunkte > NICER – Vernetzte infrastrukturlose Kooperation zur Krisenbewältigung LOEWE > LOEWE-Zentren LOEWE > LOEWE-Zentren > CRISP - Center for Research in Security and Privacy |
Hinterlegungsdatum: | 22 Jan 2019 07:13 |
Letzte Änderung: | 23 Aug 2021 12:38 |
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