• Journal of the Korea Society for Simulation
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• v.15 no.4
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• pp.1-10
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• 2006

Computer virus modeling and simulation research has conducted with focus on the network vulnerability analysis. But computer virus shows the biological virus characters such as proliferation, reproduction and evolution. Therefore it is necessary to research the computer virus modeling and simulation using the Artificial life technique. The approach of computer modeling and simulation using Artificial life provides the analysis method about the effects on the network by computer virus and the behavior mechanism of computer virus. Hence this paper proposes the methodology of computer virus modeling and simulation using Artificial life, which is effected to contribute the research on the computer virus vaccine.

• Convergence Security Journal
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• v.14 no.4
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• pp.19-26
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• 2014

Mobile malicious code is typically spread by the worm, and although modeling techniques to analyze the dispersion characteristics of the worms have been proposed, only macroscopic analysis was possible while there are limitations in predicting on certain viruses and malicious code. In this paper, prediction methods have been proposed which was based on Markov chain and is able to predict the occurrence of future malicious code by utilizing the past malicious code data. The average value of the malicious code to be applied to the prediction model of Markov chain model was applied by classifying into three categories of the total average, the last year average, and the recent average (6 months), and it was verified that malicious code prediction possibility could be increased by comparing the predicted values obtained through applying, and applying the recent average (6 months).

• Convergence Security Journal
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• v.14 no.5
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• pp.37-47
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• 2014

A Trojan malicious code is one of largest malicious codes and has been known as a virus that causes damage to a system as itself. However, it has been changed as a type that picks user information out stealthily through a backdoor method, and worms or viruses, which represent a characteristic of the Trojan malicious code, have recently been increased. Although several modeling methods for analyzing the diffusion characteristics of worms have proposed, it allows a macroscopic analysis only and shows limitations in estimating specific viruses and malicious codes. Thus, in this study an ESP model that can estimate future occurrences of Trojan malicious codes using the previous Trojan data is proposed. It is verified that the estimated value obtained using the proposed model is similar to the existing actual frequency in causes of the comparison between the obtained value and the result obtained by the Markov chain.

• Proceedings of the Korea Society for Simulation Conference
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• 2005.11a
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• pp.171-179
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• 2005

Computer virus modeling and simulation research has been conducted with focus on the network vulnerability analysis. However, computer virus generally shows the biological virus characters such as proliferation, reproduction and evolution. Therefore it is necessary to research the computer virus modeling and simulation using Artificial Life. The approach of computer modeling and simulation using the Artificial Life technology Provides the efficient analysis method for the effects on the network by computer virus and the behavioral mechanism of the computer virus. Hence this paper proposes the methodology of computer virus modeling and simulation using Artificial Life, which may be contribute the research on the computer virus vaccine.