Abstract
Detection of malicious activity in the network still is a challenge. The self-similarity feature of traffic can be used in an anomaly detection method. The influence of traffic generated by intruder who performs access attack is analyzed. In the other hands the simulation of threads is useful in designing and testing processes of a network. For this purpose a multi-layer ‘on-off’ model of traffic source is developed and a traffic generator is implemented according this model. Finally the real traffic including attacker flow is compared to the traffic generated by generator. This comparison proves that it is possible to simulate traffic similar to malicious one.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Cheng, Xie K., Wang, D.: Network traffic anomaly detection based on self-similarity using hht and wavelet transform. information assurance and security. In: Proc. 5th Inter. Conf. on Information Assurance and Security, vol. (1), pp. 710–713 (2009)
Kettani, H., Gubner, J.A.: Novel approach to the estimation of the hurst parameter in self-similar traffic. In: IEEE Conference on Local Computer Networks, pp. 1–6 (2002)
Likhanov, M., Tsybakow, B., Georganas, N.D.: Analysis of an ATM buffer with self-similar (fractal) input traffic. In: Proc IEEE INFOCOM 1995, Boston, pp. 982–985 (1995)
Mello, F.L., Lima, A.B., Lipas, M., Almeida Amazonas, J.R.: Generation of self-similar Gaussian series via wavelets for use in traffic simulations (in portuguese). IEEE Latin America Transactions 5(1), 9–20 (2007)
Papapanagiotou, I., Vardakas, J.S., Paschos, G.S., Logothetis, M.D., Kotsopoulos, S.A.: Performance evaluation of IEEE 802.11e based on ON-OFF traffic model. In: Proc. of the 3rd International Conference on Mobile Multimedia Communications, Nafpaktos, Greece, vol. 329, Article no. 17 (2007)
Rohani, M.F., Maarof, M.A., Selamat, A., Kettani, H.: Loss of self-similarity detection using exact and asymptotic self-similarity models. J. of Information Assurance and Security, 571–581 (2009)
Sarvotham, S., Riedi, R.H., Baraniuk, R.G.: Network and user driven alpha-beta On-Off source model for network traffic. Computer Networks 48(3), 335–350 (2004)
Wallis, J.R.: Robustness of the rescaled range R/S in the measurement of noncyclic long-run statistical dependence. Water Resources Research 5, 967–988 (1969)
Willinger, W., Taqqu, M., Sherman, R., Wilson, D.: Selfsimilarity through high-variability: Statistical analysis of Ethernet LAN traffic at the source level. IEEE/ACM Trans. Networking (Extended Version) 5(1), 71–86 (1997)
Willinger, W., Paxson, V., Riedi, R., Taqqu, M.: Long Range Dependence And Data Network Traffic. In: Long Range Dependence: Theory and Applications. Wiley, Chichester (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Kolbusz, J., Rozycki, P., Korniak, J. (2012). The Simulation of Malicious Traffic Using Self-similar Traffic Model. In: Hippe, Z.S., Kulikowski, J.L., Mroczek, T. (eds) Human – Computer Systems Interaction: Backgrounds and Applications 2. Advances in Intelligent and Soft Computing, vol 98. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23187-2_21
Download citation
DOI: https://doi.org/10.1007/978-3-642-23187-2_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23186-5
Online ISBN: 978-3-642-23187-2
eBook Packages: EngineeringEngineering (R0)