Modeling of Random Selfish Behavior Attack Using Single-Sided Laplacian Distribution and Performance Evaluation for High Security Communications in Mobile Ad-hoc Networks

Background: The performance of Mobile Ad-hoc Networks gets severely degraded due to various attacks including the Selfish Behaviour attack. The detection of malicious nodes and avoidance of such nodes for data forwarding is important to enhance the MANET’s performance. Methods: A probabilistic model based on Single-Sided Laplacian distribution for the random ON/OFF switching time of this attack is proposed. The model is used to make appropriate decisions regarding the assignment of trust levels to suspicious nodes. The proposed protocol, based on this trust along with Confidence values of nodes, referred to as OLSRT-C protocol is used to select the optimum path for data forwarding. Simulations are carried out using Network Simulator NS-2.35. Results: The random behavior of the Selfish Behaviour attack is analyzed by considering all the possible random parameters. The random deployment of mobile nodes, number of malicious nodes, number of times the malicious nodes switch and timing instances at which these nodes change their states are considered. From the results, it is observed that the OLSRT-C protocol gives stable performance for Packet Delivery Ratio and Routing Overheads whereas, for OLSR protocol, the Packet Delivery Ratio gradually reduces and Routing Overheads increase, for the percentage of malicious nodes increases from 10% to 50%. For OLSRT-C protocol, Average Energy Consumption per node increases marginally compared to the OLSR protocol. Conclusion: The proposed OLSRT-C protocol successfully mitigates the randomized Selfish Behaviour attack with a marginal increase in the Average Energy Consumption per node. The Protocol Efficacy for OLSRT-C protocol is much higher compared to the OLSR protocol.