Abstract:
Machine learning techniques have been achieving
significant performance improvements in various kinds of tasks,
and they are getting applied in many research fields. While
we benefit from such techniques in many ways, they can be
a serious security threat to the Internet if malicious attackers
become able to utilize them to detect software vulnerabilities. This
paper introduces a new concept of self-evolving botnets, where
computing resources of infected hosts are exploited to discover
unknown vulnerabilities in non-infected hosts. We propose a
stochastic epidemic model that incorporates such a feature of
botnets, and show its behaviors through numerical experiments.