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Displaying 1-3 out of 3 total
Multi-Domain Information Fusion for Insider Threat Detection
Found in: 2013 IEEE CS Security and Privacy Workshops (SPW2013)
By Hoda Eldardiry,Evgeniy Bart, Juan Liu,John Hanley,Bob Price,Oliver Brdiczka
Issue Date:May 2013
pp. 45-51
Malicious insiders pose significant threats to information security, and yet the capability of detecting malicious insiders is very limited. Insider threat detection is known to be a difficult problem, presenting many research challenges. In this paper we ...
An analysis of how ensembles of collective classifiers improve predictions in graphs
Found in: Proceedings of the 21st ACM international conference on Information and knowledge management (CIKM '12)
By Hoda Eldardiry, Jennifer Neville
Issue Date:October 2012
pp. 225-234
We present a theoretical analysis framework that shows how ensembles of collective classifiers can improve predictions for graph data. We show how collective ensemble classification reduces errors due to variance in learning and more interestingly inferenc...
Multi-network fusion for collective inference
Found in: Proceedings of the Eighth Workshop on Mining and Learning with Graphs (MLG '10)
By Hoda Eldardiry, Jennifer Neville
Issue Date:July 2010
pp. 46-54
Although much of the recent work in statistical relational learning has focused on homogeneous networks, many relational domains naturally consist of multiple observed networks, where each network source records a different type of relationship between the...