TU Darmstadt / ULB / TUbiblio

Lightweight Detection of Denial-of-Service Attacks on Wireless Sensor Networks Revisited

Almon, Lars and Riecker, Michael and Hollick, Matthias (2017):
Lightweight Detection of Denial-of-Service Attacks on Wireless Sensor Networks Revisited.
IEEE, In: 2017 IEEE 42nd Conference on Local Computer Networks (LCN), Singapore, 9-12 Oct. 2017, DOI: 10.1109/LCN.2017.110,
[Online-Edition: https://ieeexplore.ieee.org/document/8109386],
[Conference or Workshop Item]

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.

Item Type: Conference or Workshop Item
Erschienen: 2017
Creators: Almon, Lars and Riecker, Michael and Hollick, Matthias
Title: Lightweight Detection of Denial-of-Service Attacks on Wireless Sensor Networks Revisited
Language: English
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.

Publisher: IEEE
Uncontrolled Keywords: Wireless Sensor Networks; Denial-of-Service; Intrusion Detection
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Sichere Mobile Netze
LOEWE
LOEWE > LOEWE-Schwerpunkte
LOEWE > LOEWE-Schwerpunkte > NiCER – Networked infrastructureless Cooperation for Emergency Response
LOEWE > LOEWE-Zentren
LOEWE > LOEWE-Zentren > CRISP - Center for Research in Security and Privacy
Event Title: 2017 IEEE 42nd Conference on Local Computer Networks (LCN)
Event Location: Singapore
Event Dates: 9-12 Oct. 2017
Date Deposited: 22 Jan 2019 07:13
DOI: 10.1109/LCN.2017.110
Official URL: https://ieeexplore.ieee.org/document/8109386
Export:

Optionen (nur für Redakteure)

View Item View Item