Genetic algorithm based Internet worm propagation strategy modeling under pressure of countermeasures

Abstract

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

Malicious Botnet Survivability Mechanism Evolution Forecasting by Means of a Genetic Algorithm / Kenkėjiškų Botnet Tinklų Išgyvenamumo Mechanizmų Evoliucijos Prognozavimas Genetinio Algoritmo Priemonėmis

“…The effect of countermeasures on the evolution of the Intemet worm was discussed in (Goranin, Cenys 2009). A rather similar concept was proposed almost one year later in (Noreen et al 2009).…”

“…In (Goranin, Cenys 2008), we have proposed the GA based model dedicated to forecasting the evolution of propagation techniques used by the Intemet worms at the initial propagation phase. The effect of countermeasures on the evolution of the Intemet worm was discussed in (Goranin, Cenys 2009).…”

Information security management framework for small and medium enterprise

“…• R. Rainys researches we tied up to computer network infrastructure (Rainys, 2006;Kajackas et al, 2011); • N. Goranin proposed a genetic algorithm based model for estimating the propagation rates of known and perspective Internet worms after their propagation reaches the satiation phase (Goranin et al 2008); • S. Ramanauskaite proposes a composite denial of service attack model that combines bandwidth exhaustion, filtering, and memory depletion models for a more realistic representation of similar cyber attacks (Ramanauskaitė et al 2015); • J. Janulevicius performed analysis of virtualization and risk assessment (Janulevičius et al, 2017); • Several scientists under M.K. Ragulskis leadership performed an indepth analysis of cryptography.…”

Specialized Genetic Algorithm Based Simulation Tool Designed For Malware Evolution Forecasting

“…Although it is widely accepted that malware evolution forecasting is an important information security task, the first model-based research paper on this topic appeared only in 2008 [6], which discussed the Internet worm evolution trends. It was shown that GA may be used for malware characteristic evolution forecasting.…”