Open AccessNovel User Level Data Leakage Detection Algorithm
Author(s) -
T.Lakshmi Siva Rama Krishna,
P. Bandavi,
K. Priyanka,
V.P. Vivek
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.g5313.0881019
Subject(s) - leakage (economics) , computer science , data mining , algorithm , real time computing , economics , macroeconomics
Data leakage detection (DLD) is the most widely used detection technique in many applications such as etc. detecting data leakage by various data sources is an important research issue. Several researchers contributed to detect the data leakage by proposing various techniques. In the existing DLD techniques the performance metrics such as accuracy and time have been neglected. In this paper, we have proposed a new DLD algorithm and named it as novel user level data leakage detection algorithm (NULDLDA). In the proposed NULDLDA we have considered the user point of view to know the leakage of data by which agent among several existing agents. We have implemented and compared the NULDLDA with existing DLD. The experimental results indicate that proposed NULDLDA improved the performance over DLD with respect to time and accuracy.