Data leakage detection using dynamic data structure and classification techniques
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Guevara Maldonado, César Byron | 2015-01-05
Data leakage is a permanent problem
in public and private institutions around the world;
particularly, identifying the information leakage efficiently.
In order to solve this problem, this paper poses
an adaptable data structure based on human behavior
using all the activities executed within the computer
system. When applying this structure, the normal behavior
is modeled for each user, so in this way, detects
any abnormal behavior in real time. Moreover, this
structure enables the application of several classification
techniques such as decision trees (C4.5), UCS,
and Naive Bayes, these techniques have proven efficient
outcomes in intrusion detection. In the testing
of this model, a scenario demonstrating the proposal’s
effectiveness with real information from a government
institution was designed so as to establish future lines
of work.
LEER