A study on the trend of cloud service and security through text mining technique

  • Authors

    • Seong Taek Park
    • Sung Won Lee
    • Tae Gu Kang
    2018-06-08
    https://doi.org/10.14419/ijet.v7i2.33.13869
  • Big Data, Cloud Service, Cloud Security, Text Mining, Crawling.

  • Abstract

    Background/Objectives: The purpose of this study is to recognize the significance of security of cloud service activation and success and to draw the direction and importance for the development of Korean cloud service. Cloud computing service makes it possible to conduct a test easily and quickly at a low cost, to be scalable with an inexpensive cost, and to curb unnecessary expenses.

    Methods/Statistical analysis: This study collected news articles from NAVER with the use of crawling technique. The collected data were pre-processed (cleaned), and then 25 words with a high priority were analyzed in the category of the first half of 2015, the second half of 2015, and the first half of 2016.

    Findings: To find the trend of cloud computing service security, this study collected news articles and analyzed them after data cleaning. The analysis revealed that there was a difference in importance of each period. In the first half of 2015, the 2nd half of 2015, and the 1st half of 2016, the common noun words extracted were cloud, service, security, and enterprise in order.

    The difference was that the word 'environment' was found in the 1st half of 2015, the word 'management' in the 2nd half of 2015, and the words 'customer' and 'use' in the 1st half of 2016.

    Improvements/Applications: According to the analysis, there was a difference in importance by year. It is considered that the study results will be able to serve as the guidelines for establishing a systematic plan of cloud service security in the firms and institutions providing cloud service.

     

     

  • References

    1. [1] Park ST, Park EM, Seo JH, and Li G, Factors affecting the continuous use of cloud service: focused on security risks. Cluster Computing.2016, 19(1), pp.485-495.

      [2] Noh KS, A study on the position of CDO for improving competitiveness based big data in cluster computing environment. Cluster Computing.2016, 19(3), pp.1659-1669.

      [3] Korea Ministry of Government Legislation, Cloud Development Act, http://www.law.go.kr.

      [4] Han, J.S.: Security Threats in the Mobile Cloud Service Environment. Journal of Digital Convergence.2014, 12(5), pp.263-269.

      [5] WWDC, iCloud Storage Overview, https://developer.apple.com/videos/play/wwdc2011/501.

      [6] GOV.UK. G-Cloud suppliers' guide, https://www.gov.uk/guidance/g-cloud-suppliers-guide.

      [7] Park ST, Kim YR, Jeong SP, Hong CI, Kang TG, A Case Study on Effective Technique of Distributed Data Storage for Big Data Processing in the Wireless Internet Environment. Wireless Personal Communications.2016, 86(1), pp.239-253.

      [8] Lee BS, Kim BS, Protection of Personal Information on Cloud Service Models. Journal of the Korea Institute of Information Security and Cryptology.2015, 25(5), pp.1245-1255.

      [9] NIA. ICT new technology paradigm: Cloud computing strategy. CIO Report, 2009, 17, 1–40.

      [10] O’Neal J, NetApp, storage infrastructure for the cloud, 2009. http://www.netapp.com/us/communities/tech-ontap/tot-cloud-storage-0509.aspx.

      [11] Alqahtany S, Clarke N, Furnell S, Reich C, A forensic acquisition and analysis system for IaaS. Cluster Computing.2016, 19(1), pp.439-453.

      [12] Carretero J, Blas JG, Introduction to cloud computing: platforms and solutions. Cluster Computing.2014, 17(4),pp.1225-1229.

      [13] Kim DY, Li G, Park ST, Ko MH, A study on effects of security risks on acceptance of enterprise cloud service: moderating of employment and non-employment using PLS multiple group analysis. Journal of Computer Virology and Hacking Techniques.2016, 12(3), pp.151-161.

      [14] Ju JH, Ma SY, Moon JS, Proposal of Security Requirements for Storage Virtualization System against Cloud Computing Security Threats. Journal of Security Engineering.2014, 11(6), pp.469-478.

      [15] Noh KS, A Study on the Authentication and Security of Financial Settlement using the Finger Vein Technology in Wireless Internet Environment. Wireless Personal Communications.2016, 89(3), pp.761-775.

      [16] CSA, Cloud Security Alliance. https://downloads.cloudsecurityalliance.org/assets/research/security-guidance/csaguide.v3.0.pdf.

      [17] The Society of Digital Policy & Management. Big Data Analytics for Business. Kwangmoonkag, Seoul, 2015.

      [18] The Society of Digital Policy & Management. Introduction to Big Data Analysis Kwangmoonkag, Seoul, 2016.

      [19] Park EM, Seo JH, Ko MH, The effects of leadership by types of soccer instruction on big data analysis, Cluster Computing.2016, 19(3), pp.1647–1658.

      [20] The Society of Digital Policy & Management. Big data analysis plan. Wowpass, Seoul, 2015.

      [21] Jung SJ, Bae YM, Trend analysis of Threats and Technologies for Cloud Security. Journal of Security Engineering.2013, 10(2), pp.199-212.

      [22] Li C, Li L, Efficient Market Strategy Based Optimal Scheduling in Hybrid Cloud Environments. Wireless Personal Communications.2015, 83(1), pp.581-602.

  • Downloads

  • How to Cite

    Taek Park, S., Won Lee, S., & Gu Kang, T. (2018). A study on the trend of cloud service and security through text mining technique. International Journal of Engineering & Technology, 7(2.33), 127-132. https://doi.org/10.14419/ijet.v7i2.33.13869

    Received date: 2018-06-08

    Accepted date: 2018-06-08

    Published date: 2018-06-08