access icon free Reconstruction of C&C channel for P2P botnet

Breaking down botnets has always been a big challenge. The robustness of command and control (C&C) channels is increased, and the detection of botmaster is harder in peer-to-peer (P2P) botnets. In this study, the authors proposed a probabilistic method to reconstruct the topologies of the C&C channel for P2P botnets. Due to the geographic dispersion of P2P botnet members, it is not possible to supervise all members, and there does not exist all necessary data for applying other graph reconstruction methods. So far, no general method has been introduced to reconstruct C&C channel topology for all type of P2P botnet. In their method, the probability of connections between bots is estimated by using the inaccurate receiving times of several cascades, network model parameters of C&C channel, and end-to-end delay distribution of the Internet. The receiving times can be collected by observing the external reaction of bots to commands. The results of their simulations show that more than 90% of the edges in a 1000-member network with node degree mean 50, have been accurately estimated by collecting the inaccurate receiving times of 22 cascades. In case the receiving times of just half of the bots are collected, this accuracy of estimation is obtained by using 95 cascades.

Inspec keywords: network theory (graphs); Internet; invasive software; computer network security; peer-to-peer computing; probability; graph theory

Other keywords: probabilistic method; botmaster detection; network model parameters; peer-to-peer botnets; end-to-end delay distribution; P2P botnet members; C&C channel topology; command and control channels; 1000-member network; graph reconstruction methods; Internet; geographic dispersion

Subjects: Other computer networks; Computer communications; Other topics in statistics; Other topics in statistics; Combinatorial mathematics; Data security; Combinatorial mathematics

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