Predicting Number of Zombies in DDoS Attacks Using Pace Regression Model

B. B. Gupta


A DDoS attacker attempts to disrupt a target, by flooding it with illegitimate packets which are generated from a large number of zombies, usurping its bandwidth and overtaxing it to prevent legitimate inquiries from getting through. This paper reports the evaluation results of proposed approach that is used to predict number of zombies using Pace Regression Model. A relationship is established between number of zombies and observed deviation in sample entropy. Various statistical performance measures, such as R2, CC, SSE, MSE, RMSE, NMSE, η, MAE are used to measure the performance of the regression model. Network topologies similar to Internet used for simulation are generated using Transit-Stub model of GT-ITM topology generator. NS-2 network simulator on Linux platform is used as simulation test bed for launching DDoS attacks with varied number of zombies. The simulation results are promising as we are able to predict number of zombies efficiently using Pace Regression Model with considerably less error rate.


DDoS attack, intrusion detection, pace regression, zombies, entropy

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This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.

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