SRI International / Oak Ridge National Laboratory / MIT Press / IEEE Intelligent Systems / /
Country
United States / /
Currency
USD / / /
Facility
Princeton University / Oak Ridge Institute / North Carolina State University / Carnegie Mellon Software Engineering Institute / /
IndustryTerm
real-time rules / data mining components / real-time intrusion detection using data mining / computer systems / data mining approach / finance sector / intrusion detection systems / Real time data mining-based intrusion detection / applied data mining techniques / banking / e-crime / data mining / data mining component / law enforcement executives / real-time detection / insider threat detection systems / /
Organization
Carnegie Mellon Software Engineering Institute / U.S. Department of Energy / North Carolina State University / Raleigh / INFOSEC Research Council / MIT / Oak Ridge Institute for Science and Education / Princeton University / Department of Homeland Security / System Dynamics Society / United States Secret Service / /
Person
N. Tan / V / Sheldon al / A. L. Prodromidis / M. Miller / G. Simon / V / /
Position
administrator / analyst / /
ProvinceOrState
New Jersey / Minnesota / North Carolina / Tennessee / /
PublishedMedium
IEEE Intelligent Systems / /
Technology
expert system / LOF algorithms / data mining / machine learning / /
Detection of Undesirable Insider Behavior Joseph A. Calandrino1? , Steven J. McKinney2? , and Frederick T. Sheldon3 1 Princeton University, Princeton, NJ 08544, USA [removed]