TY - GEN
T1 - Denial of service (DoS) attacks detection in MANETs using Bayesian classifiers
AU - Rmayti, M.
AU - Begriche, Y.
AU - Khatoun, R.
AU - Khoukhi, L.
AU - Gaiti, D.
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/2/20
Y1 - 2014/2/20
N2 - Mobile Ad hoc Networks (MANETs) are dynamic and self-organized networks composed of mobile wireless entities. The communications between nodes are multihop, and provided in a decentralized way without preexisting infrastructure. These characteristics make MANETs vulnerable to many types of Denial of Service (DoS) attacks, this including, Wormhole, Blackhole and Grayhole attack. This latter targets some reactive routing protocols in the aim of disrupting the forwarding process in the network. Grayhole attack occurs during the route discovery phase when a malicious node drops some of received packets. The watchdog is a well-known intrusion detection mechanism and usually used to detect this kind of attack. However, watchdogs are characterized by a relatively high rate of false alerts. In this paper, we propose a novel approach of watchdog based on two Bayesian filters: Bernoulli and Multinomial. We use these two models in a complementary manner to successfully detect the packet dropping attacks in mobile ad hoc networks. Based on simulation results, our filters prove that these attacks can be detected with a high rate of accuracy.
AB - Mobile Ad hoc Networks (MANETs) are dynamic and self-organized networks composed of mobile wireless entities. The communications between nodes are multihop, and provided in a decentralized way without preexisting infrastructure. These characteristics make MANETs vulnerable to many types of Denial of Service (DoS) attacks, this including, Wormhole, Blackhole and Grayhole attack. This latter targets some reactive routing protocols in the aim of disrupting the forwarding process in the network. Grayhole attack occurs during the route discovery phase when a malicious node drops some of received packets. The watchdog is a well-known intrusion detection mechanism and usually used to detect this kind of attack. However, watchdogs are characterized by a relatively high rate of false alerts. In this paper, we propose a novel approach of watchdog based on two Bayesian filters: Bernoulli and Multinomial. We use these two models in a complementary manner to successfully detect the packet dropping attacks in mobile ad hoc networks. Based on simulation results, our filters prove that these attacks can be detected with a high rate of accuracy.
U2 - 10.1109/SCVT.2014.7046699
DO - 10.1109/SCVT.2014.7046699
M3 - Conference contribution
AN - SCOPUS:84988240488
T3 - Proceedings of the 2014 IEEE 21st Symposium on Communications and Vehicular Technology in the BeNeLux, IEEE SCVT 2014
SP - 7
EP - 12
BT - Proceedings of the 2014 IEEE 21st Symposium on Communications and Vehicular Technology in the BeNeLux, IEEE SCVT 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 21st IEEE Symposium on Communications and Vehicular Technology in the BeNeLux, IEEE SCVT 2014
Y2 - 10 November 2014
ER -