Genetic Algorithm Based Internet Worm Propagation Strategy Modeling

Existing malware propagation models mainly concentrate on malware epidemic consequences modeling, i.e. forecasting the number of infected computers, and are based only on current malware propagation strategies. In this article we propose a genetic algorithm based model, which aims at evaluating existing as well as modeling other potentially dangerous Internet worms’ propagation strategies. The efficiency of strategies is evaluated by applying the proposed fitness function. Genetic algorithm is selected as a modeling tool taking into consideration the efficiency of this method while solving optimization and modeling problems with large solution space. The main application of the proposed model is a countermeasures planning in advance and computer network design optimization.