Optimized Degree-Aware Random Patching for Thwarting IoT Botnets

The massive number of Device-to-Device (D2D) communication links and lack of protective programming cause Internet of Things (IoT) networks to be vulnerable to malware attacks. Botnets are formed when large number of devices get infected and controlled by the attacker. Controlled devices can be used by the attacker to launch denial of service (DoS) attacks. In the literature, population dynamics were used to model the malware propagation in IoT networks. In this letter the model is modified to include the spatial degree correlation between neighboring devices, and the defender optimization problem is updated to acquire different patching rates.