Over the past decade, the Advanced Persistent Threat (APT) has risen to forefront of cybersecurity threats. APTs are a major contributor to the billions of dollars lost by corporations around the world annually. The threat is significant enough that the Navy Cyber Power 2020 plan identified them as a “must mitigate” threat in order to ensure the security of its warfighting network.
Reports, white papers, and various other open source materials offer a plethora of information to cybersecurity professionals regarding these APT attacks and the organizations behind them but mining and correlating information out of these various sources needs the support of standardized language and a common understand of terms that comes from an accepted APT ontology.
This paper and its related research applies the science of Natural Language Processing Open Source Intelligence in order to build an open source Ontology in the APT domain with the goal of building a dictionary and taxonomy for this complex domain.
","abstract_html":"<p>Over the past decade, the Advanced Persistent Threat (APT) has risen to forefront of cybersecurity threats. APTs are a major contributor to the billions of dollars lost by corporations around the world annually. The threat is significant enough that the <em>Navy Cyber Power 2020</em> plan identified them as a “must mitigate” threat in order to ensure the security of its warfighting network.</p> <p>Reports, white papers, and various other open source materials offer a plethora of information to cybersecurity professionals regarding these APT attacks and the organizations behind them but mining and correlating information out of these various sources needs the support of standardized language and a common understand of terms that comes from an accepted APT ontology.</p> <p>This paper and its related research applies the science of Natural Language Processing Open Source Intelligence in order to build an open source Ontology in the APT domain with the goal of building a dictionary and taxonomy for this complex domain.</p>","abstract_has_math":false,"creators":["Holzer, Corey T"],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Dissertation","degree_discipline":"Computer and Information Technology","degree_department":null,"school":null,"contributors":["James E. Dietz","John A. Springer","Dongyan Xu","Biajian Yang"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-12-01T08:00:00Z","date_published":"2016-12-01T08:00:00Z","updated_at":"2026-07-24T03:54:09Z","subjects":["Information Technology","Applied sciences","Advanced persistent threat","Cybersecurity","Natural language processing","Open source intelligence"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://docs.lib.purdue.edu/open_access_dissertations/948","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["James E. Dietz","John A. Springer","Dongyan Xu","Biajian Yang"]},{"key":"dc:creator","label":"Author","values":["Holzer, Corey T"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer and Information Technology"]},{"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":["Information Technology","Applied sciences","Advanced persistent threat","Cybersecurity","Natural language processing","Open source intelligence"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://docs.lib.purdue.edu/open_access_dissertations/948"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Over the past decade, the Advanced Persistent Threat (APT) has risen to forefront of cybersecurity threats. APTs are a major contributor to the billions of dollars lost by corporations around the world annually. The threat is significant enough that the Navy Cyber Power 2020 plan identified them as a “must mitigate” threat in order to ensure the security of its warfighting network.
Reports, white papers, and various other open source materials offer a plethora of information to cybersecurity professionals regarding these APT attacks and the organizations behind them but mining and correlating information out of these various sources needs the support of standardized language and a common understand of terms that comes from an accepted APT ontology.
This paper and its related research applies the science of Natural Language Processing Open Source Intelligence in order to build an open source Ontology in the APT domain with the goal of building a dictionary and taxonomy for this complex domain.
"]},{"key":"dc:title","label":"Title","values":["The application of natural language processing to open source intelligence for ontology development in the advanced persistent threat domain"]}]}],"canonical_facts":{"dc:contributor":["James E. Dietz","John A. Springer","Dongyan Xu","Biajian Yang"],"dc:creator":["Holzer, Corey T"],"dc:description.abstract":["Over the past decade, the Advanced Persistent Threat (APT) has risen to forefront of cybersecurity threats. APTs are a major contributor to the billions of dollars lost by corporations around the world annually. The threat is significant enough that the Navy Cyber Power 2020 plan identified them as a “must mitigate” threat in order to ensure the security of its warfighting network.
Reports, white papers, and various other open source materials offer a plethora of information to cybersecurity professionals regarding these APT attacks and the organizations behind them but mining and correlating information out of these various sources needs the support of standardized language and a common understand of terms that comes from an accepted APT ontology.
This paper and its related research applies the science of Natural Language Processing Open Source Intelligence in order to build an open source Ontology in the APT domain with the goal of building a dictionary and taxonomy for this complex domain.
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