Specialized Genetic Algorithm Based Simulation Tool Designed For Malware Evolution Forecasting

Vaidas Juzonis, Nikolaj Goranin, Antanas Cenys, Dmitrij Olifer

Abstract


From the security point of view malware evolution forecasting is very important, since it provides an opportunity to predict malware epidemic outbreaks, develop effective countermeasure techniques and evaluate information security level. Genetic algorithm approach for mobile malware evolution forecasting already proved its effectiveness. There exists a number of simulation tools based on the Genetic algorithms, that could be used for malware forecasting, but their main disadvantages from the user’s point of view is that they are too complicated and can not fully represent the security entity parameter set. In this article we describe the specialized evolution forecasting simulation tool developed for security entities, such as different types of malware, which is capable of providing intuitive graphical interface for users and ensure high calculation performance. Tool applicability for the evolution forecasting tasks is proved by providing mobile malware evolution forecasting results and comparing them with the results we obtained in 2010 by means of MATLAB.

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DOI: http://dx.doi.org/10.17951/ai.2012.12.4.23-37
Data publikacji: 2012-01-01 00:00:00
Data złożenia artykułu: 2016-04-28 09:08:31

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