Implementation and comparison of machine learning classifiers for information security risk analysis of a human resources department
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Date
2010
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Publisher
Open Access Color
Green Open Access
Yes
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No
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Average
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Top 10%
Abstract
The aim of this study is threefold. First a qualitative information security risk survey is implemented in human resources department of a logistics company. Second a machine learning risk classification and prediction model with proper data set is established from the results obtained in this survey. Third several classifier algorithms are tested where their training and test performances are compared using error rates ROC curves Kappa statistics and F-measures. The results show that some classifier algorithms can be used to estimate specific human based information security risks within acceptable error rates. ©2010 IEEE. © 2011 Elsevier B.V. All rights reserved.
Description
Keywords
Classifier Algorithms, Data Sets, Error Rate, Human Resources, Human-based Information, Information Security, Kappa Statistic, Logistics Company, Machine-learning, Prediction Model, Qualitative Information, Risk Classification, Roc Curves, Test Performance, Algorithms, Classification (of Information), Classifiers, Error Statistics, Industrial Management, Industry, Information Systems, Learning Systems, Mathematical Models, Project Management, Risk Analysis, Risk Assessment, Risk Perception, Surveys, Security Of Data, Classifier algorithms, Data sets, Error rate, Human resources, Human-based information, Information security, Kappa statistic, Logistics company, Machine-learning, Prediction model, Qualitative information, Risk classification, ROC curves, Test performance, Algorithms, Classification (of information), Classifiers, Error statistics, Industrial management, Industry, Information systems, Learning systems, Mathematical models, Project management, Risk analysis, Risk assessment, Risk perception, Surveys, Security of data
Fields of Science
0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology
Citation
WoS Q
Scopus Q
OpenCitations Citation Count
8
Source
2010 International Conference on Computer Information Systems and Industrial Management Applications CISIM 2010
Volume
Issue
Start Page
187
End Page
192
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Scopus : 14
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Mendeley Readers : 27
SCOPUS™ Citations
14
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