A novel online CEP learning engine for MANET IDS - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2017

A novel online CEP learning engine for MANET IDS

Résumé

In recent years the use of wireless ad hoc networks has seen an increase of applications. A big part of the research has focused on Mobile Ad Hoc Networks (MANETs), due to its implementations in vehicular networks, battlefield communications, among others. These peer-to-peer networks usually test novel communications protocols, but leave out the network security part. A wide range of attacks can happen as in wired networks, some of them being more damaging in MANETs. Because of the characteristics of these networks, conventional methods for detection of attack traffic are ineffective. Intrusion Detection Systems (IDSs) are constructed on various detection techniques, but one of the most important is anomaly detection. IDSs based only in past attacks signatures are less effective, even more if these IDSs are centralized. Our work focuses on adding a novel Machine Learning technique to the detection engine, which recognizes attack traffic in an online way (not to store and analyze after), re-writing IDS rules on the fly. Experiments were done using the Dockemu emulation tool with Linux Containers, IPv6 and OLSR as routing protocol, leading to promising results
Fichier non déposé

Dates et versions

hal-01681466 , version 1 (11-01-2018)

Identifiants

Citer

Erick Petersen, Marco Antonio To de Leon, Stephane Maag. A novel online CEP learning engine for MANET IDS. LATINCOM 2017 : 9th IEEE Latin-American Conference on Communications, Nov 2017, Guatemala City, Guatemala. pp.1 - 6, ⟨10.1109/LATINCOM.2017.8240196⟩. ⟨hal-01681466⟩
95 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More