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The Use of Artificial Intelligence for the Intrusion Detection System in Computer Networks

  • Santiago Yip Ortuño
  • José Alberto Hernández AguilarEmail author
  • Blanca Taboada
  • Carlos Alberto Ochoa Ortiz
  • Miguel Pérez Ramírez
  • Gustavo Arroyo Figueroa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10632)

Abstract

We discuss the application of Artificial Intelligence for the design of intrusion detection systems (IDS) applied on computer networks. For this purpose, we use J48 rand Clonal-G [5] immune artificial system Algorithms, in WEKA software, with the purpose to classify and predict intrusions in KDD-Cup 1999 and Kyoto 2006 databases. We obtain for the KDD-Cup 1999 database 92.69% for ClonalG and 99.91% of precision for J48 respectively. For the Kyoto University 2006 database, we obtain 95.2% for ClonalG and 99.25% of precision for J48. Finally, based on these results we propose a model to detect intrusions using AI techniques. The main contribution of the paper is the adaptability of the CLONAL-G Algorithm and the reduction of database attributes by using Genetic Search.

Keywords

Artificial immune system ClonalG J48 Intrusion detection system Security model 

References

  1. 1.
    Al-Enezi, J.R., Abbod, M.F., Alsharhan, S.: Artificial Immune Systems - Models, Algorithms and Applications. Academic Research Publishing Agency (2010)Google Scholar
  2. 2.
    Bachmayer, S.: Artificial Immune Systems. Department of Computer Science, University of Helsinki (2008)Google Scholar
  3. 3.
    Dasgupta, D., Ji, Z., González, F.: Artificial immune system (AIS) research in the last five years. IEEE Congr. Evol. Comput. 1, 123–130 (2003)Google Scholar
  4. 4.
    Dario Duke, N., Chavarro Porras, J.C., Moreno Laverde, R.: Smart security. Scientia Et Technica 1(35) (2007)Google Scholar
  5. 5.
    Castro, L.N., Timmis, J.: Artificial Immune Systems: A New Computational Intelligence Approach. Springer, London (2002)zbMATHGoogle Scholar
  6. 6.
    Farmer, J.D., Packard, N.H., Perelson, A.S.: The immune system, adaptation, and machine learning. Elsevier Science Publishers B.V., pp. 197–204 (1986)Google Scholar
  7. 7.
    Han, J., Pei, J., Kamber, M.: Data Mining: Concepts and Techniques. Elsevier, Amsterdam (2011)zbMATHGoogle Scholar
  8. 8.
    ISO: The portal of ISO 27001 in Spanish. What is an ISMS? (2012). http://www.iso27000.es/sgsi.html
  9. 9.
    Torgo, L., Torgo, L.: Data Mining with R: Learning with Case Studies. Chapman & Hall/CRC, Boca Raton (2011)Google Scholar
  10. 10.
    Zum Herrenhaus, M., Schommer, C.: Security analysis in internet traffic through artificial immune systems. In: INTERREG IIIC/e-Bird, Workshop “Trustworthy Software”, pp. 1–9 (2006)Google Scholar
  11. 11.
    Zum Herrenhaus, M., Schommer, C.: Healthy-security analysis in Internet traffic through artificial immune systems. arXiv preprint arXiv:0805.0909 (2008)
  12. 12.
    Symantec: El gusano Stuxnet. (2010). http://www.symantec.com/es/mx/page.jsp?id=stuxnet
  13. 13.
    Neal, D.: Home Depot confirms 53 million email addresses stolen in recent hack, 7 November 2014. http://www.v3.co.uk/v3-uk/news/2380100/home-depot-confirms-53-million-email-addresses-stolen-in-recent-hack
  14. 14.
    Kaspersky Security Network Report: Ransomware in 2014–2016 (2016)Google Scholar
  15. 15.
    Whitman, M.E., Herbert, M.J.: Principles of Information Security. Cengage Learning, Boston (2011)Google Scholar
  16. 16.
    Kim, J., Bentley, P.J.: An evaluation of negative selection in an artificial immune system. In: Proceedings of GECCO, pp. 1330–1337 (2001)Google Scholar
  17. 17.
    Hernández Aguilar, J.A., Burlak, G., Lara, B.: Diseño e Implementación de un Sistema de Evaluación Remota con Seguridad Avanzada para Universidades Utilizando Minería de Datos. Comput. y Sist. 13(4), 463–473 (2010)Google Scholar
  18. 18.
  19. 19.
  20. 20.
    Yan, Q., Yu, J.: AINIDS: an immune-based network intrusion detection system. In: International Society for Optics and Photonics Defense and Security Symposium, p. 62410U, April 2006Google Scholar
  21. 21.
    Jinquan, Z., Xiaojie, L., Tao, L., Caiming, L., Lingxi, P., Feixian, S.: A self-adaptive negative selection algorithm used for anomaly detection. Prog. Nat. Sci. 19(2), 261–266 (2009)CrossRefGoogle Scholar
  22. 22.
    Levin, I.: KDD-99 classifier learning contest: LLSoft’s results overview. SIGKDD Explor. 1(2), 67–75 (2000)CrossRefGoogle Scholar
  23. 23.
    Rojas Gonzalez, I., García Gallardo, J.: Bayesian network application on information security. Res. Comput. Sci. 51, 87–98 (2010). (I.P. Nacional, Ed.)Google Scholar
  24. 24.
    Pimentel, J.C.L., Monroy, R.: Formal support to security protocol development: a survey. Comput. y Sist. 12(1), 89–108 (2008)Google Scholar
  25. 25.
    Argüelles Arellano, M.D.C.: Challenges of Cyber Law in Mexico. Comput. y Sist. 20(4), 827–831 (2016)Google Scholar
  26. 26.
    Danham, M.H., Sridhar, S.: Data mining, Introductory and Advanced Topics, 1st edn. Person education, London (2006)Google Scholar
  27. 27.
    Patil, T.R., Sherekar, S.S.: Performance analysis of Naive Bayes and J48 classification algorithm for data classification. Int. J. Comput. Sci. Appl. 6(2), 256–261 (2013)Google Scholar
  28. 28.
    Kyoto: Kyoto data (1999). http://www.takakura.com/kyoto_data/
  29. 29.
    Cutello, V., Narzisi, G., Nicosia, G., Pavone, M.: Clonal selection algorithms: a comparative study using effective mutation potentials. In: Jacob, C., Pilat, M.L., Bentley, P.J., Timmis, J.I. (eds.) Artificial Immune Systems, ICARIS 2005. LNCS, vol. 3627, pp. 13–28. Springer, Berlin (2005).  https://doi.org/10.1007/11536444_2CrossRefGoogle Scholar
  30. 30.
    AISWEB: The Online Home of Artificial Immune Systems (2017). http://www.artificial-immune-systems.org/algorithms.shtml#clonal-alg
  31. 31.

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Santiago Yip Ortuño
    • 1
  • José Alberto Hernández Aguilar
    • 1
    • 3
    Email author
  • Blanca Taboada
    • 2
  • Carlos Alberto Ochoa Ortiz
    • 3
  • Miguel Pérez Ramírez
    • 3
  • Gustavo Arroyo Figueroa
    • 3
  1. 1.Autonomous University of Morelos StateCuernavacaMexico
  2. 2.IBT-UNAMCuernavacaMexico
  3. 3.National Institute of Electricity and Clean Energies (INEEL)CuernavacaMexico

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