Advertisement

A Bio-Inspired Approach for Risk Analysis of ICT Systems

  • Aurelio La Corte
  • Marialisa Scatá
  • Evelina Giacchi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6782)

Abstract

In recent years, information and communication technology (ICT) has been characterised by several evolving trends and new challenges. The process towards the convergence has been developed to take into account new realities and new perspectives. Along with many positive benefits, there are several security concerns and ensuring privacy is extremely difficult. New security issues make it necessary to rewrite the safety requirements and to know what the risks are and what can be lost. With this paper we want to propose a bio-inspired approach as a result of a comparison between biological models and information security. The risk analysis proposed aims to address technical, human and economical aspects of the security to strategically guide security investments. This analysis requires knowledge of the failure time distribution to assess the degree of system security and analyse the existing countermeasures to decrease the risk, minimise the losses, and successfully manage the security.

Keywords

ICT VoIP NGN Risk Analysis Security Failure Time Distribution 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Leveque, V.: Information Security: A Strategic Approach. IEEE Computer Society, J. Wiley and Sons (2006)Google Scholar
  2. 2.
    Ayoama, T.: A New Generation Network: Beyond the Internet and NGN, Keio University and National institute of Information and Communications Technology, ITU-T KALEIDOSCOPE, IEEE Communications Magazine (2009)Google Scholar
  3. 3.
    VoIP Security Alliance,VoIP Security and Privacy Threat Taxonomy (2010), http://www.voipsa.org
  4. 4.
    Keromytis, A.D.: Voice-over-IP Security: Research and Practice, IEEE Computer and Reliability Societies, Secure Systems (2010)Google Scholar
  5. 5.
    Shneier, B.: Architecture of privacy. IEEE Computer Society, Security and Privacy (2009)Google Scholar
  6. 6.
    Quittek, J., Niccolini, S., Tartarelli, S., Schlegel, R.: NEC Europe Ltd, 2008 On Spam over Internet Telephony (SPIT) Prevention IEEE Communications Magazine (2008)Google Scholar
  7. 7.
    Roxbee Cox, D., Oakes, D. (eds.): Analysis of Survival data. Chapman & Hall/CRC (1984)Google Scholar
  8. 8.
    Roxbee Cox, D.: Regression Models and life-tables. Journal of the Royal Society, Series B (Methodological) 34(2) (1972)Google Scholar
  9. 9.
    International Standard ISO/IEC 27002:2005, Information Technology Security tech- niques. Code of Practice for information security managementGoogle Scholar
  10. 10.
    International Standard ISO/IEC 27005:2008, Information Technology Security techniques. Information Security Risk ManagementGoogle Scholar
  11. 11.
    Ryan, J.C.H., Ryan, D.J.: Performance Metrics for Information security Risk management. IEEE Computer Society, Security and Privacy (2008)Google Scholar
  12. 12.
    Ryan, J.C.H., Ryan, D.J.: Biological System and models in informa- tion Security. In: Proceedings of the 12th Colloquium for Information System Security Education, University of Texas, Dallas (2008)Google Scholar
  13. 13.
    Ryan, J.C.H., Ryan, D.J.: Expected benefits of information security investments, Computer and Security, ScienceDirect (2006), http://www.sciencedirect.com
  14. 14.
    Kitchovitch, S., Lió, P.: Risk perception and disease spread on social networks. In: International Conference on Computational Science (2010)Google Scholar
  15. 15.
    Lachin, J.M.: Biostatistical Methods: The Assessment of Relative Risks. John Wiley & Sons, NewYork (2000)CrossRefzbMATHGoogle Scholar
  16. 16.
    Kalbeish, J.D., Prentice, R.L.: The Statistical Analysis of Failure-Time Data, 2nd edn. Wiley, Chichester (2002)Google Scholar
  17. 17.
    Murray, W.H.: The application of epidemiology to computer viruses. Computer& Security 7(2) (1988)Google Scholar
  18. 18.
    Dressler, F., Akan, O.B.: A Survey on Bio-Inspired Networking. Elsevier Computer Networks 54(6) (2010)Google Scholar
  19. 19.
    Li, J., Knickerbocker, P.: Functional similarities between computer worms and biological pathogens. Elsevier Computer & Security (2007)Google Scholar
  20. 20.
    Meisel, M., Pappas, V., Zhang, L.: A taxonomy biologically inspired research in computer networking. Elsevier Computer Networks (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Aurelio La Corte
    • 1
  • Marialisa Scatá
    • 1
  • Evelina Giacchi
    • 1
  1. 1.Department of Electrical, Electronics and Computer Science Engineering, Faculty of EngineeringUniversity of CataniaCataniaItaly

Personalised recommendations