1 |
S. H. Woo. (2020). Attack Types and Countermeasures of Next Generation Ransomeware. Journal of the Korea Information and Communication Association Conference, 24(1), 541-544. UCI(KEPA) : I410-ECN-0101-2020-004-000905920
|
2 |
S. Venkatraman, K. Fahd, S. Kaspi & R. Venkatraman. (2016). SQL versus NoSQL movement with big data analytics. Int. J. Inform. Technol. Comput. Sci., 8, 59-66. DOI : 10.5815/ijitcs.2016.12.07
DOI
|
3 |
C. S. Bae & S. C. Goh. (2020). For Improving Security Log Big Data Analysis Efficiency, A Firewall Log Data Standard Format Proposed. Journal of the Korea Institute of Information Security and Cryptology, 30(1), 157-167. DOI : 10.13089/JKIISC.2020.30.1.157
DOI
|
4 |
J. H. Ha & T. J. Lee. (2020). Research on text mining based malware analysis technology using string information. Journal of Korea Internet Computing and Services, 21(1), 45-55. DOI : 10.7472/jksii.2020.21.1.45
DOI
|
5 |
S. K. Park. (2020). Development of Prevention and Post-recovery System against the Ransomwares Attacks using the Technique of Massively Data Signing and Kernel Level Backup. Journal of the Institute of Electronics and Information Engineers, 57(3), 57-72. DOI : 10.5573/ieie.2020.57.3.57
DOI
|
6 |
J. B. Yoo, S. J. Oh, R. H. Park & T. K. Kwon. (2018). Development Research of An Efficient Malware Classification System Using Hybrid Features And Machine Learning. Journal of the Korea Institute of Information Security & Cryptology, 28(5), 1161-1167. DOI : 10.13089/JKIISC.2018.28.5.1161
DOI
|
7 |
J. W. Lee, Y. M. Kim, J. H. Lee & J. M. Hong. (2019). An Efficient Decoy File Placement Method for Detecting Ransomware. Journal of Korean Institute of Smart Media, 8(1), 27-34. DOI : 10.30693/SMJ.2019.8.1.27
DOI
|
8 |
W. J. Joo & H. S. Kim. (2019). A Malware Variants Detection Method based on Behavior Similari. Journal of Korean Institute of Smart Media, 8(4), 25-32. DOI : 10.30693/SMJ.2019.8.4.25
DOI
|
9 |
S. I. Bae, G. B. Lee & E. G. Im. (2020). Ransomware detection using machine learning algorithms. Concurrency and Computation: Practice and Experience, 32(18). DOI : 10.1002/cpe.5422
DOI
|
10 |
J. H. Hwang & T. J. Lee. (2017). Android Malware Analysis Technology Research Based on Naive Bayes. Journal of the Korea Institute of Information Security & Cryptology, 27(5), 1087-1097. DOI : 10.13089/JKIISC.2017.27.5.1087
DOI
|
11 |
Y. B. Cho. (2018). The Malware Detection Using Deep Learning based R-CNN. Journal of Korea Digital Contents Society, 19(6), 1177-1183. DOI : 10.9728/dcs.2018.19.6.1177
DOI
|
12 |
H. J. Lee, S. Y. uh & D. S. wang. (2019). Distributed Processing System Design and Implementation for Feature Extraction from Large-Scale Malicious Code. KIPS Transactions on Computer and Communication Systems, 8(2), 2. DOI : 10.3745/KTCCS.2019.8.2.35
DOI
|
13 |
Y. S. Ko & J. P. Park. (2019). A Study on the Ransomware Detection System Based on User Requirements Analysis for Data Restoration. Journal of the Korea Academia-Industrial cooperation Society, 20(4), 50-55. DOI : 10.5762/KAIS.2019.20.4.50
DOI
|
14 |
J. G. Joo, I. S. Jung & S. H. Kang. (2019). An Optimal Feature Selection Method to Detect Malwares in Real Time Using Machine Learning. Journal of Korea Multimedia Society, 22(2), 203-209. DOI : 10.9717/kmms.2019.22.2.203
DOI
|
15 |
H. B. Kim & T. J. Lee. (2020). Stacked Autoencoder Based Malware Feature Refinement Technology Research. Journal of the Korea Institute of Information Security & Cryptology, 30(4), 593-603. DOI : 10.13089/JKIISC.2020.30.4.593
DOI
|
16 |
S. J. Kim, J. H. Ha, S. H. Oh & T. J. Lee. (2019). A Study on Malware Identification System Using Static Analysis Based Machine Learning Technique. Journal of the Korea Institute of Information Security & Cryptology, 29(4), 775-784. DOI : 10.13089/JKIISC.2019.29.4.775
DOI
|
17 |
Arvind Padmanabhan. (Date of publication). Devopedia. Structured vs Unstructured Data(Online). https://devopedia.org/structured-vs-unstructured-data
|
18 |
K. S. Kim. (2016). Performance Comparison of PostgreSQL and MongoDB using YCSB. Journal of Korean Institute of Information Scientists and Engineers, 43(12), 1385-1395. UCI(KEPA) : I410-ECN-0101-2017-569-001860058
|
19 |
Jon. P. Smith. (Date of publication). The Reformed Programmer. EF Core - Combining SQL and NoSQL databases for better performance. https://www.thereformedprogrammer.net/
|