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Automatic Security Classification with Lasso

  • Paal E. EngelstadEmail author
  • Hugo Hammer
  • Kyrre Wahl Kongsgård
  • Anis Yazidi
  • Nils Agne Nordbotten
  • Aleksander Bai
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9503)

Abstract

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.

Keywords

Classification list Machine learning Feature selection Multiclass Guard Multi-layer security Cross-domain information exchange 

Notes

Acknowledgments

This work was partially funded by the University Graduate Center (UNIK).

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Paal E. Engelstad
    • 1
    • 2
    Email author
  • Hugo Hammer
    • 2
  • Kyrre Wahl Kongsgård
    • 1
  • Anis Yazidi
    • 2
  • Nils Agne Nordbotten
    • 1
  • Aleksander Bai
    • 2
  1. 1.Norwegian Defense Research Establishement (FFI)KjellerNorway
  2. 2.Oslo and Akershus University College of Applied Sciences (HiOA)OsloNorway

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