Discovery of malicious nodes in wireless sensor networks using neural predictors
Curiac, Daniel-Ioan, Volosencu, Constantin, Doboli, Alex, Dranga, Octavian, and Bednarz, Tomasz (2007) Discovery of malicious nodes in wireless sensor networks using neural predictors. WSEAS Transactions on Computers Research, 2 (1). pp. 38-43.
|PDF (Published Version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader|
View at Publisher Website: http://www.wseas.org/
With the continuous development of the wireless devices technology, securing wireless sensor networks became more and more a significant but also a difficult task. In this paper we present our research for a robust and intelligent algorithm dedicated to the discovery of malfunctioning or attacked sensor nodes. Our strategy is focused on neural network predictors based on past and present values obtained from neighboring nodes. Limited resources in terms of computational power, energy, memory and bandwidth impose heavy constraints on functionality of an effective malfunction detection system. For this reason we consider that our algorithm is designed and suitable for execution on the base station level and, by this, it is appropriate even for large-scale sensor networks.
|Item Type:||Article (Refereed Research - C1)|
Reproduced with permission from World Scientific and Engineering Academy and Society (WSEAS).
|Keywords:||wireless sensor network; analytical redundancy; prediction; malicious node; neural network|
|FoR Codes:||10 TECHNOLOGY > 1005 Communications Technologies > 100599 Communications Technologies not elsewhere classified @ 50%|
09 ENGINEERING > 0906 Electrical and Electronic Engineering > 090699 Electrical and Electronic Engineering not elsewhere classified @ 50%
|SEO Codes:||89 INFORMATION AND COMMUNICATION SERVICES > 8999 Other Information and Communication Services > 899999 Information and Communication Services not elsewhere classified @ 100%|
|Deposited On:||28 Sep 2009 14:03|
|Last Modified:||02 Nov 2012 09:04|
Last 12 Months: 56
Repository Staff Only: item control page