DocumentCode
2315888
Title
Applying graph-based anomaly detection approaches to the discovery of insider threats
Author
Eberle, William ; Holder, Lawrence
Author_Institution
Dept. of Comput. Sci., Tennessee Technol. Univ., Cookeville, TN
fYear
2009
fDate
8-11 June 2009
Firstpage
206
Lastpage
208
Abstract
The ability to mine data represented as a graph has become important in several domains for detecting various structural patterns. One important area of data mining is anomaly detection, but little work has been done in terms of detecting anomalies in graph-based data. In this paper we present graph-based approaches to uncovering anomalies in applications containing information representing possible insider threat activity: e-mail, cell-phone calls, and order processing.
Keywords
data mining; graph theory; security of data; cell-phone call; data mining; e-mail; graph-based anomaly detection approach; Algorithm design and analysis; Application software; Computer science; Computer security; Data analysis; Data mining; Information analysis; Monitoring; Telecommunication traffic; Terrorism; anomaly detection; insider threat; minimum description length;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligence and Security Informatics, 2009. ISI '09. IEEE International Conference on
Conference_Location
Dallas, TX
Print_ISBN
978-1-4244-4171-6
Electronic_ISBN
978-1-4244-4173-0
Type
conf
DOI
10.1109/ISI.2009.5137304
Filename
5137304
Link To Document