Genetic algorithm based Internet worm propagation strategy modeling under pressure of countermeasures
Author(s) -
Nikolaj Goranin,
Antanas Čenys
Publication year - 2009
Publication title -
journal of engineering science and technology review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.19
H-Index - 28
eISSN - 1791-9320
pISSN - 1791-2377
DOI - 10.25103/jestr.021.08
Subject(s) - malware , the internet , genetic algorithm , computer science , harm , operations research , computer security , machine learning , engineering , world wide web , political science , law
Internet worms remain one of the major threats to the Internet infrastructure. Modeling allows forecasting the malware propagation consequences and evolution trends, planning countermeasures and many other tasks that cannot be investigated without harm to production systems in the wild. Existing malware propagation models mainly concentrate on malware epidemic consequences modeling, i.e. forecasting the number of infected computers, simulating malware behavior or economic propagation aspects and are based only on current malware propagation strategies. Significant research has been done in the world during the last years to fight the Internet worms. In this article we propose the extension to our genetic algorithm based model, which aims at Internet worm propagation strategies modeling under pressure of countermeasures. 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
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