DocumentCode :
1770384
Title :
Topology-dependent performance of attack graph reconstruction in PPM-based IP traceback
Author :
Kiremire, Ankunda R. ; Brust, Matthias R. ; Phoha, Vir V.
Author_Institution :
Louisiana Tech Univ., Ruston, LA, USA
fYear :
2014
fDate :
10-13 Jan. 2014
Firstpage :
363
Lastpage :
370
Abstract :
A variety of schemes based on the technique of Probabilistic Packet Marking (PPM) have been proposed to identify Distributed Denial of Service (DDoS) attack traffic sources by IP traceback. These PPM-based schemes provide a way to reconstruct the attack graph - the network path taken by the attack traffic - hence identifying its sources. Despite the large amount of research in this area, the influence of the underlying topology on the performance of PPM-based schemes remains an open issue. In this paper, we identify three network-dependent factors that affect different PPM-based schemes uniquely giving rise to a variation in and discrepancy between scheme performance from one network to another. Using simulation, we also show the collective effect of these factors on the performance of selected schemes in an extensive set of 60 Internet-like networks. We find that scheme performance is dependent on the network on which it is implemented. We show how each of these factors contributes to a discrepancy in scheme performance in large scale networks. This discrepancy is exhibited independent of similarities or differences in the underlying models of the networks.
Keywords :
computer network security; graph theory; telecommunication network routing; DDoS attack traffic sources; Internet-like networks; PPM-based IP traceback; PPM-based schemes; attack graph reconstruction; distributed denial of service attack traffic sources; large scale networks; probabilistic packet marking; topology-dependent performance; Computer crime; Convergence; IP networks; Network topology; Privacy; Topology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Consumer Communications and Networking Conference (CCNC), 2014 IEEE 11th
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4799-2356-4
Type :
conf
DOI :
10.1109/CCNC.2014.6866596
Filename :
6866596
Link To Document :
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