By Lauryn Silverhardt

Come and play on the seashore with Dora and Boots!

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In: Proc. of NSDI, pp. 43–56. USENIX/ACM (2005) 9. : Understanding BGP Misconfiguration. In: Proc. of SIGCOMM, pp. 3–16. ACM, New York (2002) 10. : Improved BGP Convergence via Ghost Flushing. In: Proc. of 22nd INFOCOM, pp. 927–937. IEEE Computer Society, Los Alamitos (2003) 11. : Detection and Diagnosis of Inter-AS Routing Anomalies by Cooperative Intelligent Agents. , Serrat, J. ) DSOM 2005. LNCS, vol. 3775. Springer, Heidelberg (2005) 12. net 13. net/ 14. org 15. : On Detection of Anomalous Routing Dynamics in BGP.

Detailed analysis of two anomalies brought us to 26 A. Sperotto, R. Sadre, and A. Pras the conclusion that, to correctly identify suspicious traffic in general, all three metrics should be taken into consideration. Our analysis also showed that, for certain classes of attacks, the choice to monitor only a single metric may still be sufficient. This is for example the case in our flow time series for ssh traffic. On the other hand, such choice entails the risk of hiding other attacks. This is, for example, the case for the dns DoS attack, which does not appear in the flow time series.

24 A. Sperotto, R. Sadre, and A. 2 0 01/08 04:00 01/08 08:00 01/08 12:00 01/08 16:00 01/08 20:00 02/08 00:00 02/08 04:00 02/08 08:00 02/08 12:00 02/08 16:00 02/08 20:00 Fig. 8. 2 Normal vs Anomalous Traffic As already for ssh, a not-anomalous interval has been chosen for sake of comparison. The dns normal time frame spans between 12:00 and 17:00 of August 1st. The large amount of bytes sent depicts a different scenario compared to the one presented in Section 3: the sharp variation in the byte and packets time series, together with the use of a large percentage of UDP packets suggests indeed the possibility of a DoS against a few number of destination hosts.

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