DocumentCode
1965254
Title
Helping intelligence analysts detect threats in overflowing, changing and incomplete information
Author
Thomere, Jerome ; Harrison, Ian ; Lowrance, John ; Rodriguez, Andres ; Ruspini, Enrique ; Wolverton, Michael
Author_Institution
Artificial Intelligence Center, SRI Int., Menlo Park, CA, USA
fYear
2004
fDate
21-22 July 2004
Firstpage
39
Lastpage
45
Abstract
An important role of intelligence organizations is to be able to identify and predict threats within a vast quantity of imprecise and noisy information. We describe the concept and function of our pattern-matching architecture, LAW (Link Analysis Workbench). This system is based upon two main ideas. The first idea is that both the data and the threats can be described in term of graphs of entities and events linked together with semantic relationships. Therefore, graph-based pattern matching techniques can be used to identify threats. The second idea is that analysts constitute an essential part of the system; LAW is designed to handle a lot of interaction with the user, particularly to help in authoring and revising patterns, by allowing analysts to understand the matching process and results.
Keywords
data analysis; graph theory; pattern matching; relational databases; security; changing information; graph-based pattern matching techniques; graph-edit distance; incomplete information; intelligence analysts; intelligence organizations; link analysis workbench; noisy information; ontologies; overflowing information; pattern-matching architecture; relational data; semantic relationships; threat detection; threat identification; Discrete event simulation; Information analysis; Information retrieval; Observability; Ontologies; Pattern analysis; Pattern matching; Relational databases;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence for Homeland Security and Personal Safety, 2004. CIHSPS 2004. Proceedings of the 2004 IEEE International Conference on
Print_ISBN
0-7803-8381-8
Type
conf
DOI
10.1109/CIHSPS.2004.1360205
Filename
1360205
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