ABSTRACT As smart devices become increasingly interconnected through the Internet, the Internet of Everything (IoE) has emerged as a foundational aspect of modern life, supporting convenience, automation, and energy management. However, many IoE devices lack sufficient security mechanisms, making them vulnerable targets for cyberattacks, particularly Distributed Denial‐of‐Service (DDoS) attacks. This research proposes a mathematical modeling framework to analyze and simulate the behavior of DDoS attacks in IoE environments. A modified SIR (Susceptible‐Infected‐Recovered) model is employed to represent device state transitions, combined with assumptions about traffic volume and device capacity, as well as theoretical theorems for developing effective defense strategies. Simulation results reveal that when the basic reproduction number exceeds 1, the system experiences rapid propagation of the attack, with the number of compromised devices increasing significantly before recovering through isolation mechanisms. Three defense strategies were compared: no defense, static defense with , and adaptive defense that adjusts dynamically based on the infection level. The results show that without defense, the system is overwhelmed and fails. Static defense fully mitigates the attack but consumes a constant level of resources. In contrast, adaptive defense effectively reduces system impact using significantly fewer resources by scaling mitigation based on real‐time threats. Visualizations such as phase diagrams, heatmaps, and cumulative cost graphs confirm the theoretical findings and illustrate the dynamics clearly. This study concludes that mathematical modeling, combined with dynamic control strategies, can significantly improve the resilience of IoE systems against DDoS attacks. The validated approach offers a practical foundation for designing scalable and adaptive cybersecurity solutions for future IoT and IoE infrastructures.
Boonyopakorn et al. (Tue,) studied this question.