Automatic Malware Detection Rule Generation and Verification System

Sungho Kim; Suchul Lee

Automatic Malware Detection Rule Generation and Verification System

Sungho Kim, Suchul Lee, Journal of Internet Computing and Services, Vol. 20, No. 2, pp. 9-19, Apr. 2019

10.7472/jksii.2019.20.2.9, Full Text:

Keywords: Malware, Detection rule, SNORT, LDA, network threat

Abstract

Service and users over the Internet are increasing rapidly. Cyber attacks are also increasing. As a result, information leakage and financial damage are occurring. Government, public agencies, and companies are using security systems that use signature-based detection rules to respond to known malicious codes. However, it takes a long time to generate and validate signature-based detection rules. In this paper, we propose and develop signature based detection rule generation and verification systems using the signature extraction scheme developed based on the LDA(latent Dirichlet allocation) algorithm and the traffic analysis technique. Experimental results show that detection rules are generated and verified much more quickly than before.

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Cite this article

[APA Style]

Kim, S. & Lee, S. (2019). Automatic Malware Detection Rule Generation and Verification System. Journal of Internet Computing and Services, 20(2), 9-19. DOI: 10.7472/jksii.2019.20.2.9.

[IEEE Style]

S. Kim and S. Lee, "Automatic Malware Detection Rule Generation and Verification System," Journal of Internet Computing and Services, vol. 20, no. 2, pp. 9-19, 2019. DOI: 10.7472/jksii.2019.20.2.9.

[ACM Style]

Sungho Kim and Suchul Lee. 2019. Automatic Malware Detection Rule Generation and Verification System. Journal of Internet Computing and Services, 20, 2, (2019), 9-19. DOI: 10.7472/jksii.2019.20.2.9.