Risk assessment

Model
Digital Document
Publisher
Florida Atlantic University
Description
At the turn of the new millennium, the focus of Information Technology Management turned to Information and Systems Security, as opposed to competitive advantage investment. In catering to the security needs of various firms and institutions, it is seen that different entities require varying Information Security configurations. This thesis attempts to utilize Risk Analysis, a commonly used procedure in business realms, to formulate customized Firewalls based on the specific needs of a network, subsequently building an effective system following the "Defense in Depth" strategy. This is done by first choosing an efficient Risk Analysis model which suits the process of creating Firewall policies, and then applying it to a particular case study. A network within Florida Atlantic University is used as an experimental test case, and by analyzing the traffic to which it is subject while behind a single Firewall layer, a specific Security Policy is arrived at and implemented.
Model
Digital Document
Publisher
Florida Atlantic University
Description
Northeastern and mid-Atlantic United States are understudied from the perspective of hurricane vulnerability. In an attempt to fill this gap in research, this dissertation attempted to assess the hurricane vulnerability of the northeastern and mid- Atlantic United States through the construction of a Composite Hurricane Vulnerability Index (CHVI) for 184 counties extending from Maine to Virginia. The CHVI was computed by incorporating indicators of human vulnerability and physical exposure. Human vulnerability was derived from demographic, social and economic characteristics whereas physical exposure was based on attributes of the natural and built up environments. The spatial distribution of the CHVI and its component indices were examined and analyzed to meet the research goals, which were a) to develop indices of human vulnerability, physical exposure and composite hurricane vulnerability for all counties; b) to assess vulnerability distribution in terms of population size, metropolitan status (metropolitan versus non metropolitan counties) and location (coastal versus inland counties); c) to identify the specific underlying causes of vulnerability; d) to identify the significant clusters and outliers of high vulnerability; and e) to examine overlaps between high human vulnerability and high physical exposure in the region. Results indicated high overall vulnerability for counties that were metropolitan and / or coastal. Vulnerability clusters and intersections pointed towards high vulnerability in the major cities along the northeastern megalopolis, in the Hampton Roads section of Virginia and in parts of Delmarva Peninsula. Evidence of relationship of population size, metropolitan status and location with vulnerability levels provides a new perspective to vulnerability assessment.