DocumentCode :
265551
Title :
Grey model and polynomial regression for identifying malicious nodes in MANETs
Author :
Silva, Anderson A. A. ; Pontes, Elvis ; Fen Zhou ; Kofuji, Sergio Takeo
Author_Institution :
Univ. Paulista, Sao Paulo, Brazil
fYear :
2014
fDate :
8-12 Dec. 2014
Firstpage :
162
Lastpage :
168
Abstract :
Nodes positioning is an essential issue for diverse applications in Mobile Ad Hoc Networks (MANETs). However, besides misbehaving nodes that could cause power depletion, MANETs are also susceptible to cyber-attacks, which can make the network unstable and/or unavailable. Therefore, considering the gaps aforementioned, the goal of this paper is to propose a model for identifying malicious/misbehaving nodes by: (1) the use of two forecasting methods (Grey Model and Polynomial Regression); (2) variability analysis; and (3) simulation of fake node positions. The obtained results allow concluding our model has high rate of accuracy for detecting malicious/misbehaving nodes.
Keywords :
forecasting theory; grey systems; mobile ad hoc networks; polynomials; regression analysis; MANET; cyber-attack; fake node position simulation; forecasting method; grey model; malicious-misbehaving node identification; mobile ad hoc network; polynomial regression; power depletion; variability analysis; Ad hoc networks; Forecasting; Mathematical model; Mobile computing; Polynomials; Predictive models; Time series analysis; Grey Theory GM(1, 1); MANET; Polynomial Regression; malicious node identification; misbehaving node detection; prediction model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Global Communications Conference (GLOBECOM), 2014 IEEE
Conference_Location :
Austin, TX
Type :
conf
DOI :
10.1109/GLOCOM.2014.7036801
Filename :
7036801
Link To Document :
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