home › event - bayesian network model for predicting insider threats

EVENT:

Bayesian Network Model for Predicting Insider Threats
Conferences & Talks

Workshop on Research for Insider Threat (WRIT)

24 May 2013
3:45-5:00pm
San Francisco, California

 

description

This paper introduces a Bayesian network model for the motivation and psychology of the malicious insider. First, an initial model was developed based on results in the research literature, highlighting critical variables for the prediction of degree of interest in a potentially malicious insider. Second, a survey was conducted to measure these predictive variables in a common sample of normal participants. Third, a structural equation model was constructed based on the original model, updated based on a split-half sample of the empirical survey data and validated against the other half of the dataset. Fourth, the Bayesian network was adjusted in light of the results of the empirical analysis. Fifth, the updated model was used to develop an upper bound on the quality of model predictions of its own simulated data. When empirical data regarding psychological predictors were input to the model, predictions of counterproductive behavior approached the upper bound of model predictiveness.

 

upcoming events   view all 

Automated Data Integration
Eric Huang, Author, Saigopal Nelaturi
27 October 2014
Conferences & Talks  

Global Competitiveness: The Role of Innovation and Productivity
Stephen Hoover, CEO, PARC
27 October 2014 | Toronto, Canada
Conferences & Talks  

The Internet of Everything
Stephen Hoover, CEO, PARC
28 October 2014 | Toronto, Canada
Conferences & Talks  

Open Forum: Cities and the Digital Frontier
Mike Steep
30 October 2014
George E. Pake Auditorium, PARC | Palo Alto, CA

Churchill Club