The application of natural language processing to open source intelligence for ontology development in the advanced persistent threat domain

<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>

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Computer and Information Technology

Year

2016

Author dc:creator

• Holzer, Corey T

Contributors dc:contributor

• James E. Dietz
• John A. Springer
• Dongyan Xu
• Biajian Yang

• Information Technology
• Applied sciences
• Advanced persistent threat
• Cybersecurity
• Natural language processing
• Open source intelligence

Repository record dc:identifier

https://docs.lib.purdue.edu/open_access_dissertations/948

OAI identifier oai:identifier

oai:docs.lib.purdue.edu:open_access_dissertations-2157