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Detecting anomaly node behavior in wireless sensor networks
Mittuniversitetet, Fakulteten för naturvetenskap, teknik och medier, Institutionen för informationsteknologi och medier. (Electronics design division, SensibleReality, SensorNetworkSecurity)
Mittuniversitetet, Fakulteten för naturvetenskap, teknik och medier, Institutionen för informationsteknologi och medier. (SensibleReality, SensorNetworkSecurity)
2007 (engelsk)Inngår i: Proceedings - 21st International Conference on Advanced Information Networking and Applications Workshops/Symposia, AINAW'07, USA: IEEE conference proceedings, 2007, Vol. 2, s. 6s. 451-456, artikkel-id 4221100Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Wireless sensor networks are usually deployed in a way "once deployed, never changed". The actions of sensor nodes are either pre-scheduled inside chips or triggered to respond outside events in the predefined way. This relatively predictable working flow make it easy to build accurate node profiles and detect any violation of normal profiles. In this paper, traffic patterns observed are used to model node behavior in wireless sensor networks. Firstly, selected traffic related features are used to translate observed packets into different events. Following this, unique patterns based on the arriving order of different packet events are extracted to form the normal profile for each sensor node during the profile learning stage. Finally, real time anomaly detection can be achieved based on the profile matching.

sted, utgiver, år, opplag, sider
USA: IEEE conference proceedings, 2007. Vol. 2, s. 6s. 451-456, artikkel-id 4221100
HSV kategori
Identifikatorer
URN: urn:nbn:se:miun:diva-8162DOI: 10.1109/AINAW.2007.148Scopus ID: 2-s2.0-35248878553ISBN: 978-0-7695-2847-3 (tryckt)OAI: oai:DiVA.org:miun-8162DiVA, id: diva2:133383
Konferanse
21st International Conference on Advanced Information Networking and ApplicationsWorkshops/Symposia, AINAW'07; Niagara Falls, ON; Canada; 21 May 2007 through 23 May 2007; Category numberP2847; Code 70261
Prosjekter
STC - Sensible Things that CommunicateTilgjengelig fra: 2009-01-09 Laget: 2009-01-09 Sist oppdatert: 2018-01-13bibliografisk kontrollert
Inngår i avhandling
1. Traffic Analysis, Modeling and Their Applications in Energy-Constrained Wireless Sensor Networks: On Network Optimization and Anomaly Detection
Åpne denne publikasjonen i ny fane eller vindu >>Traffic Analysis, Modeling and Their Applications in Energy-Constrained Wireless Sensor Networks: On Network Optimization and Anomaly Detection
2010 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

Wireless sensor network (WSN) has emerged as a promising technology thanks to the recent advances in electronics, networking, and information processing. A wide range of WSN applications have been proposed such as habitat monitoring, environmental observations and forecasting systems, health monitoring, etc. In these applications, many low power and inexpensive sensor nodes are deployed in a vast space to cooperate as a network.

Although WSN is a promising technology, there is still a great deal of additional research required before it finally becomes a mature technology. This dissertation concentrates on three factors which are holding back the development of WSNs. Firstly, there is a lack of traffic analysis & modeling for WSNs. Secondly, network optimization for WSNs needs more investigation. Thirdly, the development of anomaly detection techniques for WSNs remains a seldomly touched area.

In the field of traffic analysis & modeling for WSNs, this dissertation presents several ways of modeling different aspects relating to WSN traffic, including the modeling of sequence relations among arriving packets, the modeling of a data traffic arrival process for an event-driven WSN, and the modeling of a traffic load distribution for a symmetric dense WSN. These research results enrich the current understanding regarding the traffic dynamics within WSNs, and provide a basis for further work on network optimization and anomaly detection for WSNs.

In the field of network optimization for WSNs, this dissertation presents network optimization models from which network performance bounds can be derived. This dissertation also investigates network performances constrained by the energy resources available in an indentified bottleneck zone. For a symmetric dense WSN, an optimal energy allocation scheme is proposed to minimize the energy waste due to the uneven energy drain among sensor nodes. By modeling the interrelationships among communication traffic, energy consumption and WSN performances, these presented results have efficiently integrated the knowledge on WSN traffic dynamics into the field of network optimization for WSNs.

Finally, in the field of anomaly detection for WSNs, this dissertation uses two examples to demonstrate the feasibility and the ease of detecting sensor network anomalies through the analysis of network traffic. The presented results will serve as an inspiration for the research community to develop more secure and more fault-tolerant WSNs.

sted, utgiver, år, opplag, sider
Sundsvall: Tryckeriet Mittuniversitetet, 2010. s. 120
Serie
Mid Sweden University doctoral thesis, ISSN 1652-893X ; 78
Emneord
Wireless sensor network, traffic analysis, network optimization, anomaly detection
HSV kategori
Identifikatorer
urn:nbn:se:miun:diva-10690 (URN)978-91-86073-64-0 (ISBN)
Disputas
2010-02-03, L111, Mittuniversitetet, Holmgatan 10, 85170 Sundsvall, Sundsvall, 10:00 (engelsk)
Opponent
Veileder
Prosjekter
STC
Tilgjengelig fra: 2010-01-26 Laget: 2009-12-16 Sist oppdatert: 2018-01-12bibliografisk kontrollert

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