Abstract:
Mobile Ad Hoc network (MANET) is an autonomous collection of mobile
nodes that communicate with each other without any pre-existing infrastructure. The
lack of central authority or infrastructure and the mobility nature of MANET
environment make it more vulnerable to malicious network attack attacks than wired
networks. Black hole attack is one of the most severe security problems in MANET
routing protocols. It is an attack in which malicious node fabricating the sequence
number, hence pretending to have the shortest and freshest route to the destination and
consequently deprives data traffic from the source node, and then it chooses to drop the
packets to perform a denial-of-service attack, or alternatively uses its place on the route
as the first step in a man-in-the-middle attack. The objective of this work is to develop a
new detection and eliminate schemes for black hole attack against AODV routing
protocol in MANET. The DEAODV protocol which is use second route for message
delivery is proposed to reduce the effect of black hole attack. The proposed DEAODV
protocol show the improvement of the network performance under black hole attack. In
conventional schemes, anomaly detection is achieved by defining the normal state from
static training data. However, in MANET such static training method could not be used
efficiently because of dynamic topology and lake of centralize management security of
MANET. For detection, new anomaly-detection scheme is proposed based on a
dynamic learning process that allows the training data to be updated at particular time
intervals. The performance of the proposed schemes has been evaluated using Network
Simulator2 (NS2).The proposed dynamic anomaly-detection scheme have significantly
enhanced network performance by providing significant effectiveness in detecting the
black hole attack against AODV. A comparative study is performed to compare the
proposed scheme performance with other existing schemes in terms of detection rate
and false positive alarm. According to the results, the proposed scheme improves the
network performance with high detection rate and low false positive alarms.
