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http://dx.doi.org/10.15207/JKCS.2019.10.5.009

Analysis of Security Problems of Deep Learning Technology  

Choi, Hee-Sik (Division of Computer & Mechatronics Engineering, Sahmyook University)
Cho, Yang-Hyun (Division of Computer & Mechatronics Engineering, Sahmyook University)
Publication Information
Journal of the Korea Convergence Society / v.10, no.5, 2019 , pp. 9-16 More about this Journal
Abstract
In this paper, it will analyze security problems, so technology's potential can apply to business security area. First, in order to deep learning do security tasks sufficiently in the business area, deep learning requires repetitive learning with large amounts of data. In this paper, to acquire learning ability to do stable business tasks, it must detect abnormal IP packets and attack such as normal software with malicious code. Therefore, this paper will analyze whether deep learning has the cognitive ability to detect various attack. In this paper, to deep learning to reach the system and reliably execute the business model which has problem, this paper will develop deep learning technology which is equipped with security engine to analyze new IP about Session and do log analysis and solve the problem of mathematical role which can extract abnormal data and distinguish infringement of system data. Then it will apply to business model to drop the vulnerability and improve the business performance.
Keywords
Convergence; AI; Machine Learning; Deep Learning; Security; Business Model;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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1 NVIDIA KOREA Center. (2018. 1. 16). Computered Unified Deviced Architecture.http://blogs.nvidia.co.kr/2018/01/16/cuda-toolkit/
2 ETRI. (2016). Trends on Distributed Frameworks for Deep Learning, ETRI Article, https://ettrends.etri.re.kr/ettrends/159/0905002137/0905002137.html
3 H. Y. Choi & Y. H. Min. (2015), Intorduction to Deep Learning and Major Issues, Korea Information Proccessing Society, 22(1), 7-21
4 M. R. Choi. (2017), Artifical Intelligence Technology based on Natural Language Processing, Telecommunications Technology Association, (36), 33-37
5 S. E. Moon, S. B. Jang, J. H. Lee & J. S. Lee. (2016), Machine Learning and Deep Learning Technology Trends, Information and Telecommunication, 49-56
6 Y. H. Shin, J. S. Yun, S. H. Seo & J. M. Chung. (2017). Deployment of Network Resources for Enhancement of Disaster Response Capabilities with Deep Learning and Augmented Reality, JICS, 18(5), 69-77 DOI 10.7472/jksii.2017.18.5.69.   DOI
7 P. S. Kang & J. H. Kim. (2014. 7. 31). What is Deeep Learning, http://www.bloter.net/archives/201445
8 J. S. Yun, K. Y. Kim, Y. C. Jung, H. S. Oh & D. J. Seo. (2017). Development of Deep Learning Technologies and Applications for the Information Extraction of S&T Open Texts, Korea Institute of Science and Technology Information , 1711042891, 1-43
9 K. Maria. (2016. 11. 10). Security Solution with Machine Learning. CIO Center Article, http://www.ciokorea.com/t/21990/%EC%95%85%EC%84%B1%EC%BD%94%EB%93%9C/31931#csidx734eda637286190876b5fbcd63a16cd
10 K. Maria. (2016. 11. 10). Security Solution with Machine Learning. CIO Center Article, http://www.ciokorea.com/t/21990/%EC%95%85%EC%84%B1%EC%BD%94%EB%93%9C/31931#csidx68a1b7c636c6fd6b63e1e9482b31a7d
11 J. Y. Kim and T. W. Lee, (2016). A Study on the Development of Smart Education Using Deep Learning Algorithm, Korea Computer Information Association, 24(2), 169-171
12 K. Maria. (2016. 11. 10). CIO Center Article, http://www.ciokorea.com/t/21990/%EC%95%85%EC%84%B1%EC%BD%94%EB%93%9C/31931#csidxbd14f7f63ec4ddfa75a2c452de87a2e
13 P. S. Kang & J. H. Kim. (2014. 7. 31). What is Deeep Learning, http://www.bloter.net/archives/201445
14 J. W. Kim, H. A. Pyo, J. W. Ha, C. K. Lee & J. H. Kim. (2015). Utilizing various Deep Learning Algorithms, Electronics and Telecommunications Research Institute, 25-31
15 S. Y. Ahn & Y. M. Park & E. J. Lim & W. Choi. (2017), Trends on Distributed Frameworks for Deep Learning, Electronics and Telecommunications Trends, 31(3), 131-141