This dissertation proposes a methodology to manage and understand the risk of underwater terrorism to critical infrastructures utilizing the parameters of the risk equation. Current methods frequently rely on statistical methods, which suffer from a lack of appropriate historical data to produce distributions and do not integrate epistemic uncertainty. Other methods rely on locating subject matter experts who can provide judgment and then undertaking an associated validation of these judgments.
Using experimentation, data from unclassified successful, or near successful, underwater attacks are analyzed and instantiated as a network graph with the key characteristics of the risk of terrorism represented as nodes and the relationship between the key characteristics forming the edges. The values of the key characteristics, instantiated as the length of the edges, are defaulted to absolute uncertainty, the state where there is no information for, or against, a particular causal factor. To facilitate obtaining the value of the nodes, the Malice spectrum is formally defined which provides a dimensionless, methodology independent model to determine the value of any given parameter. The methodology produces a meta-model constructed from the relationships between the parameters of the risk equation, which determines a relative risk value.
","abstract_html":"<p>This dissertation proposes a methodology to manage and understand the risk of underwater terrorism to critical infrastructures utilizing the parameters of the risk equation. Current methods frequently rely on statistical methods, which suffer from a lack of appropriate historical data to produce distributions and do not integrate epistemic uncertainty. Other methods rely on locating subject matter experts who can provide judgment and then undertaking an associated validation of these judgments.</p> <p>Using experimentation, data from unclassified successful, or near successful, underwater attacks are analyzed and instantiated as a network graph with the key characteristics of the risk of terrorism represented as nodes and the relationship between the key characteristics forming the edges. The values of the key characteristics, instantiated as the length of the edges, are defaulted to absolute uncertainty, the state where there is no information for, or against, a particular causal factor. To facilitate obtaining the value of the nodes, the Malice spectrum is formally defined which provides a dimensionless, methodology independent model to determine the value of any given parameter. The methodology produces a meta-model constructed from the relationships between the parameters of the risk equation, which determines a relative risk value.</p>","abstract_has_math":false,"creators":["Gay, Richard J."],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Dissertation","degree_discipline":"Engineering Management & Systems Engineering","degree_department":null,"school":null,"contributors":["Patrick Hester","Andreas Tolk","Ariel Pinto","Joseph DiRenzo"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012-07-01T07:00:00Z","date_published":"2012-07-01T07:00:00Z","updated_at":"2026-07-24T03:34:25Z","subjects":["Terrorism risk","Underwater attacks","System science","Defense and Security Studies","Military and Veterans Studies","Public Policy","Risk Analysis"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["9781267736536"],"render_values":[{"text":"9781267736536","href":null,"code":true}]}]},"links":{"outbound_url":"https://digitalcommons.odu.edu/emse_etds/64","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Patrick Hester","Andreas Tolk","Ariel Pinto","Joseph DiRenzo"]},{"key":"dc:creator","label":"Author","values":["Gay, Richard J."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2019-03-14T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Engineering Management & Systems Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Terrorism risk","Underwater attacks","System science","Defense and Security Studies","Military and Veterans Studies","Public Policy","Risk Analysis"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["9781267736536","https://digitalcommons.odu.edu/emse_etds/64"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This dissertation proposes a methodology to manage and understand the risk of underwater terrorism to critical infrastructures utilizing the parameters of the risk equation. Current methods frequently rely on statistical methods, which suffer from a lack of appropriate historical data to produce distributions and do not integrate epistemic uncertainty. Other methods rely on locating subject matter experts who can provide judgment and then undertaking an associated validation of these judgments.
Using experimentation, data from unclassified successful, or near successful, underwater attacks are analyzed and instantiated as a network graph with the key characteristics of the risk of terrorism represented as nodes and the relationship between the key characteristics forming the edges. The values of the key characteristics, instantiated as the length of the edges, are defaulted to absolute uncertainty, the state where there is no information for, or against, a particular causal factor. To facilitate obtaining the value of the nodes, the Malice spectrum is formally defined which provides a dimensionless, methodology independent model to determine the value of any given parameter. The methodology produces a meta-model constructed from the relationships between the parameters of the risk equation, which determines a relative risk value.
"]},{"key":"dc:title","label":"Title","values":["Towards Managing and Understanding the Risk of Underwater Terrorism"]}]}],"canonical_facts":{"dc:contributor":["Patrick Hester","Andreas Tolk","Ariel Pinto","Joseph DiRenzo"],"dc:creator":["Gay, Richard J."],"dc:date.available":["2019-03-14T07:00:00Z"],"dc:description.abstract":["This dissertation proposes a methodology to manage and understand the risk of underwater terrorism to critical infrastructures utilizing the parameters of the risk equation. Current methods frequently rely on statistical methods, which suffer from a lack of appropriate historical data to produce distributions and do not integrate epistemic uncertainty. Other methods rely on locating subject matter experts who can provide judgment and then undertaking an associated validation of these judgments.
Using experimentation, data from unclassified successful, or near successful, underwater attacks are analyzed and instantiated as a network graph with the key characteristics of the risk of terrorism represented as nodes and the relationship between the key characteristics forming the edges. The values of the key characteristics, instantiated as the length of the edges, are defaulted to absolute uncertainty, the state where there is no information for, or against, a particular causal factor. To facilitate obtaining the value of the nodes, the Malice spectrum is formally defined which provides a dimensionless, methodology independent model to determine the value of any given parameter. The methodology produces a meta-model constructed from the relationships between the parameters of the risk equation, which determines a relative risk value.
"],"dc:identifier":["9781267736536","https://digitalcommons.odu.edu/emse_etds/64"],"dc:subject":["Terrorism risk","Underwater attacks","System science","Defense and Security Studies","Military and Veterans Studies","Public Policy","Risk Analysis"],"dc:title":["Towards Managing and Understanding the Risk of Underwater Terrorism"],"thesis:degree_discipline":["Engineering Management & Systems Engineering"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T03:34:25Z"}