Detecting unknown attacks in wireless sensor networks that contain mobile nodes

Bankovic, Zorana and Fraga Aydillo, David and Moya Fernández, José Manuel and Vallejo López, Juan Carlos (2012). Detecting unknown attacks in wireless sensor networks that contain mobile nodes. "Sensors", v. 12 (n. 8); pp. 10834-10850. ISSN 1424-8220. https://doi.org/10.3390/s120810834.

Description

Title: Detecting unknown attacks in wireless sensor networks that contain mobile nodes
Author/s:
  • Bankovic, Zorana
  • Fraga Aydillo, David
  • Moya Fernández, José Manuel
  • Vallejo López, Juan Carlos
Item Type: Article
Título de Revista/Publicación: Sensors
Date: August 2012
ISSN: 1424-8220
Volume: 12
Subjects:
Freetext Keywords: wireless sensor networks; mobility; unknown attacks; clustering algorithms; reputation systems
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Ingeniería Electrónica
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

As wireless sensor networks are usually deployed in unattended areas, security policies cannot be updated in a timely fashion upon identification of new attacks. This gives enough time for attackers to cause significant damage. Thus, it is of great importance to provide protection from unknown attacks. However, existing solutions are mostly concentrated on known attacks. On the other hand, mobility can make the sensor network more resilient to failures, reactive to events, and able to support disparate missions with a common set of sensors, yet the problem of security becomes more complicated. In order to address the issue of security in networks with mobile nodes, we propose a machine learning solution for anomaly detection along with the feature extraction process that tries to detect temporal and spatial inconsistencies in the sequences of sensed values and the routing paths used to forward these values to the base station. We also propose a special way to treat mobile nodes, which is the main novelty of this work. The data produced in the presence of an attacker are treated as outliers, and detected using clustering techniques. These techniques are further coupled with a reputation system, in this way isolating compromised nodes in timely fashion. The proposal exhibits good performances at detecting and confining previously unseen attacks, including the cases when mobile nodes are compromised.

More information

Item ID: 16823
DC Identifier: http://oa.upm.es/16823/
OAI Identifier: oai:oa.upm.es:16823
DOI: 10.3390/s120810834
Official URL: http://www.mdpi.com/1424-8220/12/8/10834
Deposited by: Memoria Investigacion
Deposited on: 07 Aug 2013 15:51
Last Modified: 21 Apr 2016 17:10
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