Feature selection with machine learning of personality differences and insider theft of information
Current strategy to detect insider threat has been heavily from technical strategy relying on analysis on large amount of data and complex data analysis. It has been proposed that putting psychological profiling or social engineering aspect into the system to detect insider threats several advantage...
Main Author: | Wibowo, Ghifari Eka |
---|---|
Other Authors: | Justin Dauwels |
Format: | Final Year Project (FYP) |
Language: | English |
Published: |
2016
|
Subjects: | |
Online Access: | http://hdl.handle.net/10356/68289 |
Similar Items
-
Game assessment tool of IP theft
by: Jia, Xiaofan
Published: (2018) -
Android theft guard
by: Chew, Wee Han
Published: (2015) -
Intelligent feature engineered-machine learning based electricity theft detection framework for labelled and unlabelled datasets
by: Hussain, Saddam
Published: (2022) -
A novel feature engineered-CatBoost-based supervised machine learning framework for electricity theft detection
by: Hussain, Saddam, et al.
Published: (2021) -
An effective scheme against insider attack
by: Chua, Ru Hui
Published: (2017)