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Improved Multilevel Security with Latent Semantic Indexing

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  • D. THORLEUCHTER
  • D. VAN DEN POEL

Abstract

Multilevel security (MLS) is specifically created to protect information from unauthorized access. In MLS, documents are assigned to a security label by a trusted subject e.g. an authorized user and based on this assignment; the access to documents is allowed or denied. Using a large number of security labels lead to a complex administration in MLS based operating systems. This is because the manual assignment of documents to a large number of security labels by an authorized user is time-consuming and error-prone. Thus in practice, most MLS based operating systems use a small number of security labels. However, information that is normally processed in an organization consists of different sensitivities and belongs to different compartments. To depict this information in MLS, a large number of security labels is necessary. The aim of this paper is to show that the use of latent semantic indexing is successful in assigning textual information to security labels. This supports the authorized user by his manual assignment. It reduces complexity by the administration of a MLS based operating system and it enables the use of a large number of security labels. In future, the findings probably will lead to an increased usage of these MLS based operating systems in organizations.

Suggested Citation

  • D. Thorleuchter & D. Van Den Poel, 2012. "Improved Multilevel Security with Latent Semantic Indexing," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/811, Ghent University, Faculty of Economics and Business Administration.
    • Handle: RePEc:rug:rugwps:12/811
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    File URL: http://wps-feb.ugent.be/Papers/wp_12_811.pdf
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    References listed on IDEAS

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    1. Moskovitch, Robert & Elovici, Yuval & Rokach, Lior, 2008. "Detection of unknown computer worms based on behavioral classification of the host," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4544-4566, May.
    2. D. Thorleuchter & D. Van Den Poel & A. Prinzie, 2011. "Analyzing existing customers’ websites to improve the customer acquisition process as well as the profitability prediction in B-to-B marketing," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 11/733, Ghent University, Faculty of Economics and Business Administration.
    3. D. Thorleuchter & D. Van Den Poel & A. Prinzie & -, 2009. "Mining Ideas from Textual Information," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 09/619, Ghent University, Faculty of Economics and Business Administration.
    4. Scott Deerwester & Susan T. Dumais & George W. Furnas & Thomas K. Landauer & Richard Harshman, 1990. "Indexing by latent semantic analysis," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 41(6), pages 391-407, September.
    5. Bompard, E. & Napoli, R. & Xue, F., 2009. "Assessment of information impacts in power system security against malicious attacks in a general framework," Reliability Engineering and System Safety, Elsevier, vol. 94(6), pages 1087-1094.
    6. D. Thorleuchter & D. Van Den Poel & A. Prinzie & -, 2010. "A compared R&D-based and patent-based cross impact analysis for identifying relationships between technologies," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 10/632, Ghent University, Faculty of Economics and Business Administration.
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    Cited by:

    1. D. Thorleuchter & D. Van Den Poel, 2013. "Weak Signal Identification with Semantic Web Mining," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 13/860, Ghent University, Faculty of Economics and Business Administration.
    2. D. Thorleuchter & D. Van Den Poel, 2013. "Semantic Compared Cross Impact Analysis," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 13/862, Ghent University, Faculty of Economics and Business Administration.
    3. D. Thorleuchter & D. Van Den Poel, 2012. "Protecting Research and Technology from Espionage," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/824, Ghent University, Faculty of Economics and Business Administration.
    4. D. Thorleuchter & D. Van Den Poel, 2013. "Quantitative Cross Impact Analysis with Latent Semantic Indexing," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 13/861, Ghent University, Faculty of Economics and Business Administration.
    5. D. Thorleuchter & D. Van Den Poel, 2012. "Technology Classification with Latent Semantic Indexing," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/814, Ghent University, Faculty of Economics and Business Administration.

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