An Algorithm to Compare Computer-security Knowledge from Different Sources

Gulnara Yakhyaeva, Olga Yasinkaya

2015

Abstract

In this paper we describe a mathematical apparatus and software implementation of a module of the RiskPanel system, aimed to compare computer-security knowledge learned from various online sources. To describe this process, we use model-theoretic formalism. The knowledge of a particular computer attack obtained from the same source is formalized as an underdetermined algebraic system, which we call a generalized case. The knowledge base is a set of generalized cases. To implement the knowledge comparison, we construct a generalized fuzzy model, the product of all algebraic systems stored in the database. We consider an algorithm for computing consistent truth values and describe a software implementation of the developed methods. The developed algorithm has polynomial complexity.

References

  1. Assali, A., Lenne, D. & Debray, B., 2013. Adaptation Knowledge Acquistion in a CBR System. International Journal on Artificial Intelligence Tools, 22(1).
  2. Baader, F., 2003. The Description Logic Handbook. Ney York: Cambridge University Press.
  3. Burger, J. et al., 2013. Model-Based Security Engineering: Managed Co-evolution of Security Knowledge and Software Models. Foundation of Security Analysis and Design VII - FOSAD 2012/2013 Tutorial Lectures. Springer Lecture Notes in Computer Science, pp. 34- 53.
  4. Console, L., Theseider, D. & Torasso, P., 1991. Towards the integration of different knowledge sources in model-based diagnosis. Trends in Artifician Intelligence, Lecture Notes in Computer Science, Volume 549, pp. 177-186.
  5. Gartner, S. et al., 2014. Maintaining requirements for long-living software systems by incorporating security knowledge. IEEE 22nd International Requirements Engineering Conference, pp. 103-112.
  6. Haddad, M. & Bozdogan, K., 2009. Knowledge Integration in Large-Scale Organizations and Networks - Conceptual Overviev and Operational Definition. [Online] Available at: http://dx.doi.org/ 10.2139/ssrn.1437029
  7. Kolodner, J., 1992. An introduction to Case-based reasoning. Artificial Intelligence Review, Volume 6, pp. 3-34.
  8. Malykh, A. & Mantsivoda, A., 2010. Query Language for Logic Architectures. Perspectives of System Informatics: Proceedings of 7th International Conference. Lecture Notes in Computer Science, Volume 5947, pp. 294-305.
  9. Mitra, P., Wiederhold, G. & Jannink, J., 1999. Semiautomatic Integration of Knowledge Sources. Sunnyvale, CA, July 6-8, 2-nd International Conference on Information Fusion.
  10. Palchunov, D., 2008. The solution of the problem of information retrieval based on ontologies. Bisnesinformatika, 1(1), pp. 3-13.
  11. Pulchunov, D., 2009. Knowledge search and production: creation of new knowledge on the basis of natural language text analysis. Filosofiya nayki, 43(4), pp. 70- 90.
  12. Pulchunov, D. & Yakhyaeva, G., 2005. Interval fuzzy algebraic systems. Proceedings of the Asian Logic Conference , pp. 23-37.
  13. Pulchunov, D. & Yakhyaeva, G., 2010. Fuzzy algebraic systems. Vestnik NGU. Seriya: Matematica, mexanika, informatika, 10(3), pp. 75-92.
  14. Pulchunov, D., Yakhyaeva, G. & Hamutskya, A., 2011. Software system for information risk manadgement "RiskPanel". Programmnaya ingeneriya, Volume 7, pp. 29-36.
  15. Ruhroth, T. et al., 2014. Towards Adaptation and Evolution of Domain-Specific Knowledge for Maintaining Secure Systems. 15th International Conference on Product-Focused Software Process Improvement, Springer Lecture Notes in Computer Science, pp. 239-253.
  16. Steier, D., Lewis, R., Lehman, J. & Zacherl, A., 1993. Combining multiple knowledge sources in an integrated intelligent system. IEEE Expert, 8(3), pp. 35-44.
  17. Thayse, F., 1989. From Modal Logic to Deductive Databases: Introduction a Logic Based Approach to Artificial Intelligence. Chichester: Wiley.
  18. Yakhyaeva, G., 2007. Fuzzy model truth values. Bratislava, Proceedings of the 6-th International Conference Aplimat, pp. 423-431.
  19. Yakhyaeva, G. & Yasinskaya, O., 2012. The application of precedent model methodology in the riskmanagement system aimed at early detection of computer attacks. Vestnik NGU. Seriya: Informationnie Texnologii, 10(2), pp. 106-115.
  20. Yakhyaeva, G. & Yasinskaya, O., 2014. Application of Case-based Methodology for Early Diagnosis of Computer Attacks. Journal of Computing and Information Technology, 22(3), p. 145-150.
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Paper Citation


in Harvard Style

Yakhyaeva G. and Yasinkaya O. (2015). An Algorithm to Compare Computer-security Knowledge from Different Sources . In Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-096-3, pages 565-572. DOI: 10.5220/0005347205650572


in Bibtex Style

@conference{iceis15,
author={Gulnara Yakhyaeva and Olga Yasinkaya},
title={An Algorithm to Compare Computer-security Knowledge from Different Sources},
booktitle={Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2015},
pages={565-572},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005347205650572},
isbn={978-989-758-096-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - An Algorithm to Compare Computer-security Knowledge from Different Sources
SN - 978-989-758-096-3
AU - Yakhyaeva G.
AU - Yasinkaya O.
PY - 2015
SP - 565
EP - 572
DO - 10.5220/0005347205650572