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Table 1.

The number of DDoS attacks and the average cost of attacks.

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Table 1 Expand

Table 2.

The number of bots and the source of botnet DDoS attacks in 2022.

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Table 2 Expand

Fig 1.

Illustration of model compartment links.

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Fig 1 Expand

Table 3.

The description of the system’s parameters (Fig 1).

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Table 3 Expand

Table 4.

Malware types used in DDoS attacks on IoT devices.

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Table 4 Expand

Table 5.

Comparison of related works based on Essential Elements (EE).

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Table 5 Expand

Table 6.

Tools used in this study.

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Table 6 Expand

Fig 2.

Simulated network for 2000 devices.

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Fig 2 Expand

Fig 3.

Simulated network for interactions between attackers and targets (330 devices).

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Fig 3 Expand

Fig 4.

Comparison of stochastic (Monte Carlo) and deterministic solutions for the dynamics of attackers and IoT devices.

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Fig 4 Expand

Fig 5.

The reproduction number of attacking population analysis.

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Fig 5 Expand

Fig 6.

The reproduction number RTarget of targeted population analysis.

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Fig 7.

PRCC elasticity analysis of .

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Fig 8.

PRCC of analysis.

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Fig 9.

Sensitivity analysis of the reproduction number R0 to key parameters.

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Fig 9 Expand

Fig 10.

Sensitivity analysis of Ma (malicious attackers) to .

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Fig 11.

R0>1 compartment analysis when we have successful attack.

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Fig 11 Expand

Fig 12.

R0<1 compartment analysis when the cyberattack failed.

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Fig 12 Expand

Fig 13.

The proportion of compromised devices during a cyber IoT attack.

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Fig 14.

An optimal control strategy for firewall protection fp

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Fig 15.

Comparison of attacker and target populations with and without control strategy.

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