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The rapid proliferation of Internet of Things (IoT) devices in recent yearshas resulted in a significant surge in the number of cyber-attacks targetingthese devices. Recent data indicates that the number of such attacks hasincreased by over 100 percent, highlighting the urgent need for robustcybersecurity measures to mitigate these threats. In addition, a cyber-attackwill begin to spread malware across the network once it has successfullycompromised an IoT network. However, to mitigate this attack, a new patch mustbe applied immediately. In reality, the time required to prepare and apply thenew patch can vary significantly depending on the nature of the cyber-attack.In this paper, we address the issue of how to mitigate cyber-attacks before thenew patch is applied by formulating an optimal control strategy that reducesthe impact of malware propagation and minimise the number of infected devicesacross IoT networks in the smart home. A novel node-based epidemiological modelsusceptible, infected high, infected low, recover first, and recovercomplete(SI_HI_LR_FR_C) is established with immediate response state for therestricted environment. After that, the impact of malware on IoT devices usingboth high and low infected rates will be analyzed. Finally, to illustrate themain results, several numerical analyses are carried out in addition tosimulate the real-world scenario of IoT networks in the smart home, we built adataset to be used in the experiments.

Optimal Control of Malware Propagation in IoT Networks