Analysis of Behavioral Characteristics of Multiple Blackhole Attacks with TCP and UDP Connections in Mobile ADHOC Networks based on Machine Learning Algorithms
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Abstract
In Mobile Adhoc Networks (MANET’s), a suit of nodes which are under mobility work together to transmit data packets in a multiple-hop manner without relying on any fixed or centralized infrastructure. A significant obstacle in managing these networks is identifying malicious nodes, or "black holes". To detect black holes, we proposed a method involves broadcasting a Cseq to the neighboring nodes and awaiting the node's response is utilized. This Network is simulated with 25 number of nodes connected with TCP connection and observed the different behavioural characteristics of nodes. Then the connections are changed to UDP and observed the characteristics. Then characteristics are analyzed with different machine learning algorithms. The network is simulated in NS2 environment.
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