Abstract
Recently, as the rapid development of the Internet enabled easy downloading of diverse files, the number of cases of file download from unreliable paths has been increasing. This situation is advantageous in that accessibility to information is improved while being disadvantageous in that there is no defense against exposure to malware. The present paper proposes a method of judging whether programs are malicious based on Cuckoo Sandbox, which is a dynamic malware analysis system and classify the programs by comparing malware programs collected and classified in advance based on the dynamic API call counts of the programs.
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. NRF-2016R1A2B1012652, the MSIP(Ministry of Science, ICT and Future Planning, Korea, under the ITRC (Information Technology Research Center) support program (IITP-2016-R2718-16-0035) supervised by the IITP (National IT Industry Promotion Agency), the Basic Science Research Program through the NRF funded by the Ministry of Education (NRF-2015R1C1A1A02037561) and the 2016 Yeungnam University Research Grant.
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References
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Cuckoo Sandbox. http://www.cuckoosandbox.com
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Kim, J., Lee, S., Youn, J.M., Choi, H. (2017). A Study of Simple Classification of Malware Based on the Dynamic API Call Counts. In: Park, J., Pan, Y., Yi, G., Loia, V. (eds) Advances in Computer Science and Ubiquitous Computing. UCAWSN CUTE CSA 2016 2016 2016. Lecture Notes in Electrical Engineering, vol 421. Springer, Singapore. https://doi.org/10.1007/978-981-10-3023-9_147
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DOI: https://doi.org/10.1007/978-981-10-3023-9_147
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