A Flow-Based Advanced Rule Generation for Detecting User Action in SaaS Application 


Vol. 48,  No. 8, pp. 959-969, Aug.  2023
10.7840/kics.2023.48.8.959


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  Abstract

Recently, with the development of network technology, interest in applications based on cloud services is increasing. Among various cloud services, SaaS (Software as a Service) is most actively used, and is widely used by large corporations such as Google and Microsoft. SaaS is provided in the form of a subscription, and since the amount varies depending on the license, usage period, number of users,etc., research on user action detection is being conducted. In our previous study, a rule-based action detection method was proposed. However, in previous research, when generating rules, there is a problem in that they show low performance for specific applications because the dependence on SNI information is high. Therefore, in this paper, we proposed an advanced rule generation method that can solve the problems of the existing method detection performance with previous study in this study.

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  Cite this article

[IEEE Style]

J. Park, U. Baek, C. Shin, J. Choi, Y. H. Hong, T. Ho, M. Kim, "A Flow-Based Advanced Rule Generation for Detecting User Action in SaaS Application," The Journal of Korean Institute of Communications and Information Sciences, vol. 48, no. 8, pp. 959-969, 2023. DOI: 10.7840/kics.2023.48.8.959.

[ACM Style]

Jee-Tae Park, Ui-Jun Baek, Chang-Yui Shin, Jung-Woo Choi, Yoon Hwan Hong, Tae-Gyu Ho, and Myung-Sup Kim. 2023. A Flow-Based Advanced Rule Generation for Detecting User Action in SaaS Application. The Journal of Korean Institute of Communications and Information Sciences, 48, 8, (2023), 959-969. DOI: 10.7840/kics.2023.48.8.959.

[KICS Style]

Jee-Tae Park, Ui-Jun Baek, Chang-Yui Shin, Jung-Woo Choi, Yoon Hwan Hong, Tae-Gyu Ho, Myung-Sup Kim, "A Flow-Based Advanced Rule Generation for Detecting User Action in SaaS Application," The Journal of Korean Institute of Communications and Information Sciences, vol. 48, no. 8, pp. 959-969, 8. 2023. (https://doi.org/10.7840/kics.2023.48.8.959)
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pISSN : 1226 - 4717
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