Abstract
Thanks to the development of IT technology, information systems have been growing continuously. However, there are threats behind the convenience. There is a possibility of malicious users to steal sensitive information and malware can lead to social chaos by paralyzing the information systems. Several solutions to prevent these attacks have been introduced. In this paper, we introduce malware detection technique using Minhash and evaluate the performance of it and suggest the cyber quarantine system applied this technique. It contributes to detect not only known malware but unknown malware.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bergeron, J., Debbadi, M., Desharnais, J., Erhioui, M.M., Lavoie, Y., Tawbi, N.: Static detection of malicious code in executable programs (2001)
Das, A., Datar, M., Garg, A.: Google news personalization: scalable online collaborative filtering (2007)
Han, B., Choi, Y., Bae, B.: Generating malware DNA to classify the similar malwares. J. Korea Inst. Inf. Secur. Cryptology 23, 679–694 (2013)
Lee, S., Chung, T.: Proposal of malicious code classification system using MinHash in network quarantine using SDN. Korea Soc. Digital Ind. Inf. Manage. (2015)
Kim, N., Jung, J., Song, Y., Kim, H., Chung, T.: The design of SDN quarantined network. Korea Inf. Process. Soc. (2014)
Nath, H.V., Mehtre, B.M.: Static malware analysis using machine learning methods. In: MartÃnez Pérez, G., Thampi, S.M., Ko, R., Shu, L. (eds.) SNDS 2014. CCIS, vol. 420, pp. 440–450. Springer, Heidelberg (2014). doi:10.1007/978-3-642-54525-2_39
Acknowledgments
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2010-0020210).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Lee, SH., Song, MU., Jung, JK., Chung, TM. (2017). A Study of Malicious Code Classification System Using MinHash in Network Quarantine Using SDN. 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_91
Download citation
DOI: https://doi.org/10.1007/978-981-10-3023-9_91
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-3022-2
Online ISBN: 978-981-10-3023-9
eBook Packages: EngineeringEngineering (R0)