Skip to main content

Advertisement

SpringerLink
Log in

Analysis of information leakage from encrypted Skype conversations

  • Regular Contribution
  • Published:
International Journal of Information Security Aims and scope Submit manuscript

Abstract

Voice over IP (VoIP) has experienced a tremendous growth over the last few years and is now widely used among the population and for business purposes. The security of such VoIP systems is often assumed, creating a false sense of privacy. This paper investigates in detail the leakage of information from Skype, a widely used and protected VoIP application. Experiments have shown that isolated phonemes can be classified and given sentences identified. By using the dynamic time warping (DTW) algorithm, frequently used in speech processing, an accuracy of 60% can be reached. The results can be further improved by choosing specific training data and reach an accuracy of 83% under specific conditions. The initial results being speaker dependent, an approach involving the Kalman filter is proposed to extract the kernel of all training signals.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Aggarwal, C.C., Han, J., Wang, J., Yu, P.S.: A framework for clustering evolving data streams. In: VLDB 2003: Proceedings of the 29th International Conference on Very Large Data Bases, pp. 81–92. Morgan Kaufmann (2003)

  2. Aggarwal, C.C., Olshefski, D., Saha, D., Shae, Z.Y., Yu, P.: CSR: speaker recognition from compressed VoIP packet stream. In: ICME 2005: Proceedings of the IEEE International Conference on Multimedia & Expo, pp. 970–973. IEEE Computer Society, Los Alamitos, CA, USA (2005)

  3. Brookner E.: Tracking and Kalman Filtering Made Easy. Wiley, New York (1998)

    Book  Google Scholar 

  4. Chang, Y.C., Chen, K.T., Wu, C.C., Lei, C.-L.: Inferring speech activity from encrypted Skype traffic. In: Proceedings of IEEE Globecom 2008. IEEE Computer Society, Los Alamitos, CA, USA (2008)

  5. Fu A.W.C., Keogh E., Lau L.Y.H., Ratanamahatana C.A., Wong R.C.W.: Scaling and time warping in time series querying. VLDB J. 17(4), 899–921 (2008)

    Article  Google Scholar 

  6. Grewal M.S., Andrews A.P.: Kalman Filtering: Theory and Practice Using MATLAB. 3rd edn. Wiley, New York (2008)

    Google Scholar 

  7. Kalman R.E.: A new approach to linear filtering and prediction problems. Transaction of the ASME. J. Basic Eng. 82(Series D), 35–45 (1960)

    Google Scholar 

  8. Kalman R.E., Bucy R.S.: New results in linear filtering and prediction theory. Transactions of the ASME. J. Basic Eng. 83(Series D), 95–107 (1961)

    MathSciNet  Google Scholar 

  9. Keogh, E.J., Pazzani, M.J.: Derivative dynamic time warping. In: 1st SIAM International Conference on Data Mining. SIAM (2001)

  10. Lella, T., Bettati, R.: Privacy of encrypted voice-over-IP. In: SMC’07: Proceedings of the 2007 IEEE International Conference on Systems, Man and Cybernetics, pp. 3063–3068. IEEE Computer Society (2007)

  11. Salvador S., Chan P.: FastDTW: toward accurate dynamic time warping in linear time and space. Intell. Data Anal. 11(5), 561–580 (2007)

    Google Scholar 

  12. Simon D.: Kalman filtering. Embed. Syst. Program. 14(6), 72–79 (2001)

    Google Scholar 

  13. Simon D.: Optimal State Estimation: Kalman, H ∞, and Nonlinear Approaches. Wiley, New York (2006)

    Google Scholar 

  14. Simon D.: Using nonlinear Kalman filtering to estimate signals. Embed. Syst. Design. 19(7), 38–53 (2006)

    Google Scholar 

  15. Welch, G., Bishop, G.: An introduction to the Kalman filter. Tech. Rep. TR 95-041, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA (2006)

  16. WinDump: Official website. http://www.winpcap.org/windump (2010)

  17. Wright, C.V., Ballard, L., Coull, S.E., Monrose, F., Masson, G.M.: Spot me if you can: uncovering spoken phrases in encrypted VoIP conversations. In: SP’08: Proceedings of the 29th IEEE Symposium on Security and Privacy, pp. 35–49. IEEE Computer Society, Washington, DC, USA (2008)

  18. Wright, C.V., Ballard, L., Monrose, F., Masson, G.M.: Language identification of encrypted VoIP traffic: Alejandra y Roberto or Alice and Bob? In: SS’07: Proceedings of the 16th USENIX Security Symposium, pp. 1–12. USENIX Association, Berkeley, CA, USA (2007)

Download references

Author information

Authors and Affiliations

  1. Centre for Secure Information Technologies (CSIT), Queen’s University of Belfast, Belfast, Northern Ireland, UK

    Benoît Dupasquier, Stefan Burschka, Kieran McLaughlin & Sakir Sezer

Authors
  1. Benoît Dupasquier
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Stefan Burschka
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kieran McLaughlin
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sakir Sezer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Benoît Dupasquier.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Dupasquier, B., Burschka, S., McLaughlin, K. et al. Analysis of information leakage from encrypted Skype conversations. Int. J. Inf. Secur. 9, 313–325 (2010). https://doi.org/10.1007/s10207-010-0111-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10207-010-0111-4

Keywords

Search

Navigation