Grey Model and Polynomial Regression for Identifying Malicious Nodes in MANETs
| dc.contributor.author | Silva, Anderson A. A. [UNESP] | |
| dc.contributor.author | Pontes, Elvis | |
| dc.contributor.author | Zhou, Fen | |
| dc.contributor.author | Kofuji, Sergio Takeo | |
| dc.contributor.author | IEEE | |
| dc.contributor.institution | Universidade de São Paulo (USP) | |
| dc.contributor.institution | Univ Avignon | |
| dc.contributor.institution | Universidade Estadual Paulista (Unesp) | |
| dc.date.accessioned | 2019-10-03T18:18:36Z | |
| dc.date.available | 2019-10-03T18:18:36Z | |
| dc.date.issued | 2014-01-01 | |
| dc.description.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. | en |
| dc.description.affiliation | Univ Sao Paulo, LSI POLI, BR-05508 Sao Paulo, Brazil | |
| dc.description.affiliation | Univ Avignon, CERI LIA, Avignon, France | |
| dc.description.affiliation | Univ Estadual Paulista, Unip, Sao Paulo, Brazil | |
| dc.description.affiliationUnesp | Univ Estadual Paulista, Unip, Sao Paulo, Brazil | |
| dc.format.extent | 162-168 | |
| dc.identifier.citation | 2014 Ieee Global Communications Conference (globecom 2014). New York: Ieee, p. 162-168, 2014. | |
| dc.identifier.issn | 2334-0983 | |
| dc.identifier.uri | http://hdl.handle.net/11449/183950 | |
| dc.identifier.wos | WOS:000369900400027 | |
| dc.language.iso | eng | |
| dc.publisher | Ieee | |
| dc.relation.ispartof | 2014 Ieee Global Communications Conference (globecom 2014) | |
| dc.rights.accessRights | Acesso aberto | |
| dc.source | Web of Science | |
| dc.subject | Grey Theory GM(1,1) | |
| dc.subject | Polynomial Regression | |
| dc.subject | MANET | |
| dc.subject | misbehaving node detection | |
| dc.subject | malicious node identification | |
| dc.subject | prediction model | |
| dc.title | Grey Model and Polynomial Regression for Identifying Malicious Nodes in MANETs | en |
| dc.type | Trabalho apresentado em evento | |
| dcterms.license | http://www.ieee.org/publications_standards/publications/rights/rights_policies.html | |
| dcterms.rightsHolder | Ieee |