Automatic Security Classification with Lasso
With an increasing amount of generated information, also within security domains, there is a growing need for tools that can assist with automatic security classification. The state-of-the art today is the use of simple classification lists (“dirty word lists”) for reactive content checking. In the future, however, we expect there will be both proactive tools for security classification (assisting humans when creating the information object) and reactive tools (i.e. double-checking the content in a guard). This paper demonstrates the use of machine learning with Lasso (Least Absolute Shrinkage and Selection Operator) [1, 2] both to two-class (binary) and multi-class security classification. We also explore the ability of Lasso to create sparse solutions that are easy for humans to analyze and interpret, in contrast to many other machine learning techniques that do not possess an explanatory nature.
KeywordsClassification list Machine learning Feature selection Multiclass Guard Multi-layer security Cross-domain information exchange
This work was partially funded by the University Graduate Center (UNIK).
- 3.Nicolls, W.: Implementing company classification policy with the S/MIME security label. RFC 3114, IETF, May 2002Google Scholar
- 4.UCDMO. Ucdmo cross domain baseline list. http://www.crossdomain.org (2011). Accessed 26 March 2015
- 5.Brown, J.D., Charlebois, D.: Security classification using automated learning (scale), DRDC Ottawa CR, Technical Report (2010)Google Scholar
- 8.Mathkour, H., Touir, A., Al-Sanie, W.: Automatic information classifier using rhetorical structure theory. In: Kłopotek, M.A., Wierzchoń, S.T., Trojanowski, K. (eds.) Intelligent Information Processing and Web Mining. Advances in Soft Computing, vol. 31, pp. 229–236. Springer, Heidelberg (2005)CrossRefGoogle Scholar
- 9.Clark, K.: Automated security classification. Master’s thesis, Vrije Universiteit (2008)Google Scholar
- 10.Digitial national security archive. http://nsarchive.chadwyck.com/home.do. Accessed 26 March 2015
- 11.Abbyy. http://www.abbyy.com/. Accessed 26 March 2015
- 12.Baeza-Yates, R., Ribeiro-Neto, B., et al.: Modern Information Retrieval, vol. 463. ACM Press, New York (1999)Google Scholar