Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

An advanced data leakage detection system analyzing relations between data leak activity

Authors
Seo, M.-J.Kim, M.-H.
Issue Date
Nov-2017
Publisher
Research India Publications
Keywords
Apriori algorithm; Convolutional neural network; Data leakage detection; Generating data leakage detection scenario; Security log analysis
Citation
International Journal of Applied Engineering Research, v.12, no.21, pp.11546 - 11554
Journal Title
International Journal of Applied Engineering Research
Volume
12
Number
21
Start Page
11546
End Page
11554
URI
http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/7285
ISSN
0973-4562
Abstract
In order to prevent the data leakage by the internal staff, the companies protect important information of the company by inputting the behavior pattern related to the data leakage into the system in advance and by defining the employee as the staff who leaked the data, whose behavior pattern is detected when such inputted behavior pattern is detected. However, in the case of the existing system, if the data is leaked according to the pattern of the security log occurrence which is not inputted into the system, whether of the data leakage cannot be properly detected. Therefore, this study proposes a system to prevent the leakage of data in a data leakage pattern that is not input to the system by defining a set of security logs that can appear simultaneously at the time of data leakage through association analysis algorithm as a data leakage judgment scenario. As a result of experimenting the function of the system suggested, this study judged whether of data leakage with higher accuracy than the data leak detection system which does not apply association analysis algorithm, also it showed lower percentage of false positive and false Negative. This suggests that the proposed system is less likely to misjudge data leakage. © Research India Publications.
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Information Technology > School of Software > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Kim, Myung  Ho photo

Kim, Myung Ho
College of Information Technology (School of Software)
Read more

Altmetrics

Total Views & Downloads

BROWSE