2013
DOI: 10.1007/s11235-013-9788-9
|View full text |Cite
|
Sign up to set email alerts
|

A cluster-based countermeasure against blackhole attacks in MANETs

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
8
0

Year Published

2015
2015
2021
2021

Publication Types

Select...
8
1

Relationship

0
9

Authors

Journals

citations
Cited by 19 publications
(9 citation statements)
references
References 11 publications
0
8
0
Order By: Relevance
“…Clustering based approach is proposed in [37] for the prevention of black-hole attack in which the network is divided into clusters and cluster head (CH) is elected from the cluster for the detection of black hole attacks locally. The authors have used three parameters to give weight to each node for the election of the cluster head.…”
Section: Clustering Based Schemesmentioning
confidence: 99%
“…Clustering based approach is proposed in [37] for the prevention of black-hole attack in which the network is divided into clusters and cluster head (CH) is elected from the cluster for the detection of black hole attacks locally. The authors have used three parameters to give weight to each node for the election of the cluster head.…”
Section: Clustering Based Schemesmentioning
confidence: 99%
“…The paper [Shi et al, 2014] (AHP-E) describes a multi-attribute model for application of countermeasures against malicious attacks to nodes of mobile ad hoc networks (MANETs), for e.g. in military, emergency or mining operations, using a cluster-based strategy; the AHP methodology is used to choose 'cluster head' nodes which are supposed to implement the countermeasures, by weighting the three selected technical criteria.…”
Section: Network Planning and Designmentioning
confidence: 99%
“…Fei Shi et.al [6] provides a cluster-based scheme form preventing black hole attacks in MANETs. It first employee's a powerful analytic hierarchy process (AHP) methodology to elect cluster heads (CHs).…”
Section: Survey Of Black Hole Detection Techniques S a Arunmozhmentioning
confidence: 99%