A toolkit for detecting technical surprise.
The detection of a scientific or technological surprise within a secretive country or institute is very difficult. The ability to detect such surprises would allow analysts to identify the capabilities that could be a military or economic threat to national security. Sandia's current approach utilizing ThreatView has been successful in revealing potential technological surprises. However, as data sets become larger, it becomes critical to use algorithms as filters along with the visualization environments. Our two-year LDRD had two primary goals. First, we developed a tool, a Self-Organizing Map (SOM), to extend ThreatView and improve our understanding of the issues involved in working with textual data sets. Second, we developed a toolkit for detecting indicators of technical surprise in textual data sets. Our toolkit has been successfully used to perform technology assessments for the Science & Technology Intelligence (S&TI) program.
- Research Organization:
- Sandia National Laboratories
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 1011203
- Report Number(s):
- SAND2010-7392
- Country of Publication:
- United States
- Language:
- English
Similar Records
Hybrid methods for cybersecurity analysis :
Graph algorithms in the titan toolkit.
Putting Security in Context: Visual Correlation of Network Activity with Real-World Information
Technical Report
·
Tue Dec 31 23:00:00 EST 2013
·
OSTI ID:1147641
Graph algorithms in the titan toolkit.
Technical Report
·
Thu Oct 01 00:00:00 EDT 2009
·
OSTI ID:1001014
Putting Security in Context: Visual Correlation of Network Activity with Real-World Information
Conference
·
Wed Jun 04 00:00:00 EDT 2008
·
OSTI ID:949135