Security Systems Engineering Architectural Model:For Assessing Enterprise Networks: Application For Neural Networks

Abstract

Information sharing and joint collaboration are common practices among both commercial and government enterprises, but as individual systems become more complex, tools for assessing legacy systems - and for the purposes of this dissertation, specifically Department of Defense (DoD) military systems - fall short. Part of the problem stems from the fact that tools that were once adequate for the design and development of these legacy systems are now failing in the U.S. military's evolving net-centric systems. New, up-to-date tools need to be identified and developed to address the challenges faced with assessing legacy tools. This dissertation presents a security system engineering architecture assessment tool - the Security System Engineering Enterprise Architectural and Model (SSEEAM) - specifically tailored to meet the needs of the DoD's military community. SSEEAM is a guided information decision model that overlays system engineering principles and processes into the DoD acquisition development process. It will provide quantifiable parameters for assessing DoD security architectures from operational, managerial, and technical perspectives. The SSEEAM tool has been applied to multiple DoD agency projects for this dissertation; however, the tool cannot be validated using information related to those projects because the DoD project information is classified and proprietary. Instead, this model will be validated using the integrated Network Enhancement Telemetry (iNET) project as representative of classified DoD projects. INET is a net-centric telemetry network program for the DoD that has readily published information that is mapped into the SSEEAM tool.