Date of Award

6-2006

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Electrical and Computer Engineering

First Advisor

Robert F. Mills, PhD

Abstract

Trusted employees pose a major threat to information systems. Despite advances in prevention, detection, and response techniques, the number of malicious insider incidents and their associated costs have yet to decline. There are very few vulnerability and impact models capable of providing information owners with the ability to comprehensively assess the effectiveness an organization's malicious insider mitigation strategies. This research uses a multi-dimensional approach: content analysis, attack tree framework, and an intent driven taxonomy model are used to develop a malicious insider Decision Support System (DSS) tool. The DSS tool's utility and applicability is demonstrated using a notional example. This research gives information owners data to more appropriately allocate scarce security resources.

AFIT Designator

AFIT-GIA-ENG-06-06

DTIC Accession Number

ADA453929

Share

COinS