Web malware spread modelling and optimal control strategies.

Area of Science:

• Computer Science
• Network Security
• Epidemiology

Background:

• The internet's growth fuels increasing web threats and malware propagation.
• Accurate mathematical models are crucial for predicting and mitigating malicious link spread.
• Understanding human intervention's impact is key to controlling web malware.

Purpose of the Study:

• To investigate web malware propagation mechanisms and the effect of human intervention.
• To propose a novel differential epidemic model for analyzing malicious link spread.
• To develop optimal control strategies for malware immunization.

Main Methods:

• A new differential epidemic model extending the SIR model with a delitescent compartment.
• Theoretical analysis of model dynamics and calculation of the spreading threshold.
• Application of optimal control theory to determine cost-effective immunization strategies.

Main Results:

• The proposed model effectively captures web malware spreading behavior.
• Theoretical analysis confirms the model's dynamics and existence of optimal solutions.
• Numerical simulations demonstrate the efficacy of proposed control strategies.

Conclusions:

• The novel epidemic model provides insights into web malware propagation.
• Optimal control strategies can significantly reduce economic losses from malware infections.
• Effective malware control is achievable through informed parameter choices and strategic interventions.