Deducing Malicious Attacks in Disruption Tolerant Networks

The intermittent connectivity between nodes to transfer data is exploited using Disruption tolerant networks (DTNs).DTNs are susceptible to flood attacks which limits the network resources. A technique to detect a node has violated its rate limits. Although it is easy to detect the violation of rate limit on the internet and in telecommunication networks where the egress router and base station can account each user’s traffic , it is challenging in DTNs due to lack of communication infrastructure and consistent connectivity. A node moves around and may send data to any contacted node; it is very difficult to count the number of packets or replicas sent out by this node. If an attacker floods more packets or replicas than its limit it has to use the same count in more than one claim according to pigeonhole principle , and this inconsistency may lead to detection .The more traffic an attacker floods , the more likely it will be detected. The detection probability can be flexibly adjusted by system parameters that control the amount of claims exchanged in a contact .To overcomes the probability detection; we introduce the new concept of self –adaptive approach, where the link capacity of each packet is calculated using previous history values and then packets