JOURNAL BROWSE
Search
Advanced SearchSearch Tips
On the Training Time of Machine Learners for Automatic Classification in Multi-Level Security Systems
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
On the Training Time of Machine Learners for Automatic Classification in Multi-Level Security Systems
Engelstad, Paal E.;
  PDF(new window)
 Abstract
This paper investigates the importance of the computational overhead when machine learning methods, such as SVM, LASSO, AdaBoosting and AdaBagging, are used for automatic security classification.
 Keywords
Multi-level security;Classification;Machine learning;Ensemble methods;Feature selection;
 Language
English
 Cited by
 References
1.
(2015) Ensemble learning. see: Article (CrossRef Link). Accessed: 2015-09-18.

2.
M. Bowles. (2014) Ensemble packages in r. see: Article (CrossRef Link). Accessed: 2015-09-18.

3.
J. D. Brown and D. Charlebois, "Security classification using automated learning (scale)", DRDC Ottawa CR, Tech. Rep., 2010.

4.
P. E. Engelstad et al., "Automatic security classification with lasso", Proceedings of The 16th International Workshop on Information Security Applications (WISA 2015 ), Jeju Island, Korea, August 20-22, 2015.

5.
P. E. Engelstad, H. L. Hammer, A. Yazidi, and A. Bai, "Advanced classification lists (dirty word lists) for automatic security classification," Proceedings of The 7th IEEE International Conference on Cyberenabled distributed computing and knowledge discovery (CyberC, 2015), Cyber Security and Privacy (CSP), Xian, China, Sept 17-19, 2015.

6.
P. E. Engelstad, H. L. Hammer, A. Yazidi, and A. Bai, "Analysis of time-dependencies in automatic security classification", Proceedings of The 7th IEEE International Conference on Cyber-enabled distributed computing and knowledge discovery (CyberC, 2015), Cyber Security and Privacy (CSP), Xian, China, Sept 17-19, 2015.

7.
Y. Yang and J. Pedersen, "A comparative study on feature selection in text categorization", Proceedings of ICML-97, 14th International Conference on Machine Learning, Nashville, 1997.