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SASM- An Approach towards Self-protection in Grid Computing

  • Inderpreet Chopra
  • Maninder Singh
Part of the Communications in Computer and Information Science book series (CCIS, volume 141)

Abstract

In recent years grid which facilitates the sharing and integration of large scale heterogenous resources has been recognized as the future framework of distributed computing. Modern software is plagued by security flaws at many levels. Implementation of an autonomic system provides an inherent self-managing capability to the system overcoming the shortcomings of the manual system. This paper presents a new self-protection model- SASM based upon few principles of genetics.

Keywords

Grid Computing Intrusion Detection Intrusion Detection System Grid Environment Autonomic Computing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Mohamed, Y.A., Abdulla, A.B.: Immune Inspired Framework for Securing Hybrid MANET. In: ISIEA. IEEE, Los Alamitos (2009)Google Scholar
  2. 2.
    Claudel, B., De Palma, N., Lachaize, R., Hagimont, D.: Self-protection for Distributed Component-Based Applications. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  3. 3.
    Nou, R., Julia, F., Torres, J.: The need for self-managed access nodes in grid environments. IEEE, EASe (2007)CrossRefGoogle Scholar
  4. 4.
    Romberg, M.: The unicore grid infrastructure (2002), http://www.unicore.org
  5. 5.
    Sotomayor, B., Childers, L.: Globus Toolkit 4: Programming Java Services (2005)Google Scholar
  6. 6.
    Guo, H., Gao, J., Zhu, P., Zhang, F.: A Self-Organized Model of Agent-Enabling Autonomic Computing for Grid Environment. In: 6th Word Congress on Inteligent Control (2006)Google Scholar
  7. 7.
    Ganek, A.: Overview of Autonomic Computing: Origins. In: Evolution, Direction. CRC Press, Boca Raton (2004)Google Scholar
  8. 8.
    Kephart, J.O., Chess, D.M.: The Vision of Autonomic Computing. IEEE Computer (2003)Google Scholar
  9. 9.
    Humphrey, M., Thompson, M.: Security Implications of Typical Grid Computing Usage Scenarios. Cluster Computing 5(3) (2002)Google Scholar
  10. 10.
    Li, W.: Using Genetic Algorithm for Network Intrusion Detection. In: Proceedings of the United States Department of Energy Cyber Security Group (2004)Google Scholar
  11. 11.
    Hartmut, P.: Genetic and Evolutionary Algorithms: Principles, Methods, and Algorithms. In: Genetic and Evolutionary Algorithm Toolbox (2003)Google Scholar
  12. 12.
    Stopping insider attacks: how organizations can protect their sensitive information (September 2006), ibm.com/services
  13. 13.
    Claudel, B., De Palma, N., Lachaize, R., Hagimont, D.: Self-protection for Distributed Component-Based Applications. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  14. 14.
    Chopra, I., Singh, M.: Agent based Self-Healing System for Grid Computing. In: ICWET, pp. 31–35. ACM, New York (2010)CrossRefGoogle Scholar
  15. 15.
    Foster, I., Kesselman, C., Nick, J.M., Tuecke, S.: The physiology of the Grid. Global Grid Forum (2002)Google Scholar
  16. 16.
    Hariri, S., Qu, G., et al.: Quality-of-Protection (QoP)-An Online Monitoring and Self-Protection Mechanism. IEEE Journal on Selected Areas in Communications 23(10) (2005)Google Scholar
  17. 17.
    Horn, P.: Autonomic computing: IBM’s perspective on the state of information technology (2001), http://www.research.ibm.com/autonomic/
  18. 18.
    Humphrey, M., Thompson, M.: Security Implications of Typical Grid Computing Usage Scenarios. Cluster Computing 5(3) (July 2002)Google Scholar
  19. 19.
    Foster, I., Kesselman, C., Tuecke, S.: The anatomy of the Grid. John Wiley and Sons, Chichester (2003)CrossRefGoogle Scholar
  20. 20.
    Wang, J., Liu, X., Chien, A.: Empirical Study of Tolerating Denial-of-Service Attacks with a Proxy Network. In: Proceedings of the 14th Conference on USENIX Security Symposium (2005)Google Scholar
  21. 21.
    Ferreira, L., Berstis, V., et al.: Introduction to Grid Computing with Globus, IBM, http://www.liv.ac.uk/escience/beowulf/IBM_globus.pdf
  22. 22.
    Montero, R.S.: The Grid Way Meta-Scheduler. In: Open Source Grid and Cluster, Oakland, CA (May 2008)Google Scholar
  23. 23.
    Parashar, M., Hariri, S.: Autonomic Computing: An Overview. Springer, Heidelberg (2005)Google Scholar
  24. 24.
    Tesauro, G., Chess, D.M., Walsh, W.E., Das, R., et al.: A Multi-Agent Systems Approach to Autonomic Computing. In: AAMAS 2004. ACM, New York (2004)Google Scholar
  25. 25.
    Kreibich, C., Crowcroft, J.: Honeycomb - Creating Intrusion Detection Signatures Using Honeypots. ACM SIGCOMM (January 2004)Google Scholar
  26. 26.
    Chakrabarti, A.: Grid Computing Security, ch. 6, p. 105. Springer, Heidelberg (2007)CrossRefzbMATHGoogle Scholar
  27. 27.
  28. 28.
    Stephen, M., Sukumaran Nair, V.S., Abraham, J.: Distributed Computing Grids- Safety and Security. In: Security in Distributed, Grid, Mobile, and Pervasive Computing, ch. 14Google Scholar
  29. 29.
    Chakrabarti, A.: Grid Computing Security, ch. 8, p. 159. Springer, Heidelberg (2007)CrossRefzbMATHGoogle Scholar
  30. 30.
    Kenny, S., Coghlan, B.: Towards a Grid-Wide Intrusion Detection System. In: Advances in Grid Computing, pp. 275–284. Springer, Heidelberg (2005)Google Scholar
  31. 31.
    Schulter, A., Navarro, F., Koch, F., Westphall, C.: Towards Gridbased Intrusion Detection. In: 10th IEEE/IFIP, Network Operations and Management Symposium, NOMS 2006, pp. 1–4 (2006)Google Scholar
  32. 32.
    Witold Jarmo lkowicz, M.: A Grid-aware Intrusion Detection System, Technical University of Denmark, IMM-THESIS-2007-109Google Scholar
  33. 33.
    Leu, F.-Y., Li, M.-C., Lin, J.-C.: Intrusion Detection based on Grid. In: ICCGI 2006 (2006)Google Scholar
  34. 34.
    Srinivas, M., Patnaik, L.M.: Genetic algorithms: A survey. IEEE Computer 27(6), 17–26 (1994)CrossRefGoogle Scholar
  35. 35.
    Li, W.: Using Genetic Algorithm for Network Intrusion Detection. In: Proceedings of the United States Department of Energy Cyber Security Group (2004)Google Scholar
  36. 36.
    Brennan, M.P.: Using Snort For a Distributed Intrusion Detection System. SANS Institute (2002)Google Scholar
  37. 37.
    Sallay, H., AlShalfan, K.A., Fredj, O.B.: A scalable distributed IDS Architecture for High speed Networks. IJCSNS 9(8) (August 2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Inderpreet Chopra
    • 1
  • Maninder Singh
    • 1
  1. 1.Computer Science DepartmentThapar UniversityPatialaIndia

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