Name
Abstract | ||
|---|---|---|
Manet security has a lot of open issues. Due to its characteristics, this kind of network needs preventive and corrective protection. In this paper, we focus on corrective protection proposing an anomaly IDS model for Manet. The design and development of the IDS are considered in our 3 main stages: normal behavior construction, anomaly detection and model update. A parametrical mixture model is used for behavior modeling from reference data. The associated Bayesian classification leads to the detection algorithm. MIB variables are used to provide IDS needed information. Experiments of DoS and scanner attacks validating the model are presented as well. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11872153_16 | PWC |
Keywords | Field | DocType |
behavior modeling,bayesian classification,mobile ad hoc network,reference data,mixture model,anomaly detection | Mobile ad hoc network,Reference data (financial markets),Data mining,Anomaly detection,Naive Bayes classifier,Computer security,Computer science,Intrusion detection system,Mixture theory,Mixture model,Distributed computing | Conference |
Volume | ISSN | ISBN |
4217 | 0302-9743 | 3-540-45174-9 |
Citations | PageRank | References |
9 | 0.64 | 11 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ricardo Staciarini Puttini | 1 | 114 | 16.74 |
| Maíra Hanashiro | 2 | 9 | 0.98 |
| Fábio Miziara | 3 | 9 | 0.64 |
| Rafael T. de Sousa Jr. | 4 | 37 | 4.53 |
| L. Javier García-villalba | 5 | 99 | 17.80 |
| Cláudia Jacy Barenco | 6 | 9 | 0.98 |