Digging into IP Flow Records with a Visual Kernel Method - Computational Intelligence in Security for Information Systems - page 108

Higher values of CC also indicate that good peers have smaller average shortest
path length between them. In the simulation, the diameter of the initial network is
taken as 5. At the end of one simulation run, if there is no path between a pair of peers
using community edges, then the length of the shortest path between that pair is as-
sumed to be arbitrarily long, say 15 (used in Fig. 7). The average shortest path dis-
tance (ASPD) decreases for both honest and malicious nodes. However, the rate and
the extent of decrease for honest peers are much higher due to the formation of se-
mantic communities. For malicious peers, after an initial fall, the value of ASPD
increases consistently and finally reaches the maximum value of 15. On the other
hand, the average value of ASPD for honest peers is observed to be around 6. Since
the honest nodes are connected with shorter paths, the query propagations will also
faster for these nodes. This justifies the smaller value of TTL used in the simulation.
5 Conclusion
In this paper, a mechanism is proposed that solves multiple problems in peer-to-peer
network e.g., inauthentic download, and poor search scalability and combating free
riders. It is shown that by topology adaptation, it is possible to isolate the malicious
peers while providing topologically advantageous positions to the good peers so that
good peers get faster and authentic responses to their queries. Simulation results have
demonstrated that the protocol is robust in presence of a large percentage of malicious
peers. Analysis of message overhead of the protocol constitutes a future plan of work.
References
1. Risson, J., Moors, T.: Survey of Research Towards Robust Peer-to-Peer Networks. Com-
puter Networks 50(7), 3485-3521 (2006)
2. Schafer, J., Malinks, K., Hanacek, P.: Peer-to-Peer Networks Security. In: Proc. of the 3 rd
Int. Conf. on Internet Monitoring and Protection (ICIMP), pp. 74-79 (2008)
3. de Mello, E.R., van Moorsel, A., da Silva Fraga, J.: Evaluation of P2P Search Algorithms
for Discovering Trust Paths. In: Wolter, K. (ed.) EPEW 2007. LNCS, vol. 4748, pp. 112-
124. Springer, Heidelberg (2007)
4. Li, X., Wang, J.: A Global Trust Model of P2P Network Based on Distance-Weighted Rec-
ommendation. In: Proc. of IEEE Int. Conf. of Networking, Architecture and Storage, pp.
281-284 (2009)
5. Condie, T., Kamvar, S.D., Garcia-Molina, H.: Adaptive Peer-to-Peer Topologies. In: Proc.
of the 4 th Int. Conf. on Peer-to-Peer Computing (P2P 2004), pp. 53-62 (2004)
6. Tain, H., Zou, S., Wang, W., Cheng, S.: Constructing Efficient Peer-to-Peer Overlay To-
pologies by Adaptive Connection Establishment. Computer Communication 29(17), 3567-
3579 (2006)
7. Crespo, A., Garcia-Molina, H.: Semantic Overlay Networks for P2P Systems. Technical
Report, Stanford University (2002)
8. Schlosser, M.T., Condie, T.E., Kamvar, S.D., Kamvar, A.D.: Simulating a P2P File-Sharing
Network. In: Proc. of the 1 st Workshop on Semantics in P2P and Grid Computing (2002)