Node-based epidemic modeling for countermeasure strategies against future malware evolution

In this paper, we propose a node-based epidemic model for a countermeasure strategy against future malware evolution. The proposed epidemic model constructs a countermeasure group to suppress the infection spreading of malware. The countermeasure group aims to discover and repair software vulnerabilities through distributed machine learning using the computing resources of hosts belonging to the countermeasure group. The proposed epidemic model gives infection dynamics of malware under the situation where the countermeasure group works, considering network structures. We discuss the infection trend under this situation through numerical calculation.