Modeling of countermeasure against self-evolving botnets

Machine learning has been widely used and achieved considerable results in various research areas. On the other hand, machine learning becomes a big threat when malicious attackers make use it for the wrong purpose. As such a threat, self-evolving botnets have been considered in the past. The self-evolving botnets autonomously predict vulnerabilities by implementing machine learning with computing resources of zombie computers. Furthermore, they evolve based on the vulnerability, and thus have high infectivity. In this paper, we consider several models of Markov chains to counter the spreading of the self-evolving botnets. Through simulation experiments, this paper shows the behaviors of these models.