- Link:
- http://cscjournals.org/csc/manuscript/Journals/IJCSS/volume4/Issue6/IJCSS-369.pdf
- Collection:
-
- Subjects
- Wireless Sensor Network Distributed Data Mining Machine learning Anomaly Detection.
- Creators:
- Muktikanta Sa, Manas Ranjan Nayak&Amiya Kumar Rath Muktikanta Sa, Manas Ranjan Nayak & Amiya Kumar
Rath
- Source
- International Journal of Computer Science and Security
- Publisher
- Computer Science Journals
- Description
- Wireless Sensor networks (WSN) is a promising
technology for current as well asfuture. There is vast use of WSN
in different fields like military surveillance andtarget tracking,
traffic management, weather forecasting, habitat
monitoring,designing smart home, structural and seismic monitoring,
etc. For successapplication of ubiquitous WSN it is important to
maintain the basic security, bothfrom external and internal attacks
else entire network may collapse. Maintainingsecurity in WSN
network is not a simple job just like securing wireless
networksbecause sensor nodes are deployed in randomize manner.
Hence majorchallenges in WSN are security. In this paper we have
discussed differentattacks in WSN and how these attacks are
efficiently detected by using our agentbased model. Our model
identifies the abnormal event pattern sensor nodes in alargely
deployed distributed sensor network under a common anomaly
detectionframework which will be designed by agent based learning
and distributed datamining technique.
- Source
- International Journal of Computer Science and
Security
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