Date of Award
3-2005
Document Type
Thesis
Degree Name
Master of Science
Department
Department of Electrical and Computer Engineering
First Advisor
Robert F. Mills, PhD
Abstract
The insider threat poses a significant risk to any network or information system. A general definition of the insider threat is an authorized user performing unauthorized actions, a broad definition with no specifications on severity or action. While limited research has been able to classify and detect insider threats, it is generally understood that insider attacks are planned, and that there is a time period in which the organization's leadership can intervene and prevent the attack. Previous studies have shown that the person's behavior will generally change, and it is possible that social network analysis could be used to observe those changes. Unfortunately, generation of social network data can be a time consuming and manually intensive process. This research discusses the automatic generation of such data from computer-mediated communication records. Using the tools developed in this research, raw social network data can be gathered from communication logs quickly and cheaply. Ideas on further analysis of this data for insider threat mitigation are then presented.
AFIT Designator
AFIT-GCS-ENG-05-19
DTIC Accession Number
ADA435252
Recommended Citation
Sung Yee, Jason Wei, "Efficient Generation of Social Network Data from Computer-Mediated Communication Logs" (2005). Theses and Dissertations. 3855.
https://scholar.afit.edu/etd/3855