NDLI: Identifying threatening networks from transactional data

Content Provider	IEEE Xplore Digital Library
Author	Hitt, L. McClain, M.
Copyright Year	2013
Description	Author affiliation: 21CT, Inc., Austin, TX, USA (Hitt, L.; McClain, M.)
Abstract	We present a method for identifying threatening networks from vast amounts of transactional data (source, destination, timestamp). Our approach builds upon 21CT's patented network discovery algorithm, and analyzes the changes and trends in network activity in response to stimuli (e.g., key events) as a means to expose the adversarial nature of networks. We provide an analyst with a ranking of networks according to suspiciousness and also various graphical depictions of the change in activity patterns and anomaly scores over time. This assists the analyst in identifying networks of interest from among vast amounts of data and enables the analyst to focus time and resources on those networks. By our approach using anomaly detection, it is not necessary to have an a priori determination of what behavior constitutes a threat. We present results of our capability on real operational data that contains ground truth. Within this dataset are thirteen detected networks, four of which are known to be threatening. There are three key events in this dataset: the arrival of the U.S. Marines to the region, the removal of a key threatening leader, and the raid of an insurgent's home. Our results indicate that threatening networks conduct communications activity differently than non-threatening networks in response to key events and our approach is able to capture these differences with compelling accuracy, sensitivity, and specificity.
Sponsorship	IEEE Intelligent Transp. Syst. Soc.
Starting Page	267
Ending Page	267
File Size	325937
Page Count	1
File Format	PDF
ISBN	9781467362146
e-ISBN	9781467362139
DOI	10.1109/ISI.2013.6578835
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis behavior patterns Social network services graph analysis threat detection Vectors anomaly detection computational social science Accuracy Sensitivity social network analysis Market research Principal component analysis
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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