Date of Award
Spring 3-3-2018
Degree Type
Thesis
Degree Name
Master of Public Administration (MPA)
Abstract
The continuous evaluation (CE) of cleared Department of Defense (DoD) personnel is crucial to national security. The DoD has a CE program to identify new issues and concerns for DoD personnel and contractors requiring a secret or top-secret security clearance. This paper explores potential methods and technologies in which the DoD can utilize to improve the current CE program. The current CE system, the Automated Continuous Evaluation System (ACES) has been operational since December 2015. This study addresses the methods and technologies the ACES program should utilize to improve efficiency and security. The literature review addresses how machine learning can contribute to data analysis within the ACES program. The potential impact of this research hopes to encourage the DoD to utilize modern technology to improve the current CE program. Qualitative and quantitative research method approaches were used to gather information to produce an answer to the research hypothesis -- the DoD will increase security and efficiency by utilizing machine learning in the ACES program. The purpose of this study is to demonstrate how machine learning will improve the DoD’s CE system.
Recommended Citation
Karim, Wisam, "Improving the Continuous Evaluation of Cleared Department of Defense Personnel" (2018). EMPA Capstones. 166.
https://digitalcommons.law.ggu.edu/capstones/166