DocumentCode
119633
Title
Detecting suspicious behavior using a graph-based approach
Author
Mookiah, Lenin ; Eberle, William ; Holder, Lawrence
Author_Institution
Tennessee Tech University
fYear
2014
fDate
25-31 Oct. 2014
Firstpage
357
Lastpage
358
Abstract
The ability to discover illicit behaviour in complex, heterogeneous data is a daunting problem. In the VAST 2014 competition, one of the challenges involves identifying for local law enforcement which employees are involved and where they should be concentrating their efforts. One approach to handling this problem is a graph-based approach. In this paper, we present a graph-based anomaly detection approach for discovering suspicious employees and geographic locations.
Keywords
graph-based anomaly detection; knowledge discovery;
fLanguage
English
Publisher
ieee
Conference_Titel
Visual Analytics Science and Technology (VAST), 2014 IEEE Conference on
Conference_Location
Paris, France
Type
conf
DOI
10.1109/VAST.2014.7042564
Filename
7042564
Link To Document