Uniform node sampling service robust against collusions of malicious nodes

Proceedings of the International Conference on Dependable Systems and Networks

Volumn , Issue , 2013, Pages

  Anceaume, Emmanuelle ^a   Busnel, Yann ^b   Sericola, Bruno ^c  

^a CAMPUS DE BEAULIEU   (France)

^b INSTITUT DE RECHERCHE EN COMMUNICATIONS ET CYBERNÉTIQUE DE NANTES   (France)

^c INRIA   (France)

Author keywords

Data stream; Markov chains; randomized approximation algorithm; strong adversary; uniform sampling

Indexed keywords

DATA STREAM; EXTENSIVE SIMULATIONS; INPUT STREAMS; MALICIOUS NODES; NODE IDENTIFIERS; RANDOMIZED APPROXIMATION; STRONG ADVERSARY; UNIFORM SAMPLING;

APPROXIMATION ALGORITHMS;

MARKOV PROCESSES;

EID: 84883444309     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/DSN.2013.6575363     Document Type: Conference Paper

References (27)

1. Q. Lv, P. Cao, E. Cohen, K. L i, and S. Shenker, "Search and Replication in Unstructured Peer-to-Peer Networks," in Proceedings of the International Conference on Supercomputing (ICS), 2002, pp. 84-95.
2. Bollobas, Random Graphs-2nd Edition. Cambridge University Press, 200 1.
3. A. Demers, D. Greene, C. Hauser, W. Irish, J. Larson, S. Shenker, H. Sturgis, D. Swinehart, and D. Terry, "Epidemic algorithms for replicated database mangement," in Proceedings of the 6th ACM Symposium on Principles of Distributed Computing (PODC), 1 987.
4. L. Massoulie, E. L. Merrer, A.-M. Kermarrec, and A. Ganesh, "Peer Counting and Sanlpling in Overlay Networks: Random Walk Methods," in Proceedings of the 25th Annual Symposium on Principles of Distributed Compltling (pODC). ACM Press, 2006, pp. 1 23-132.
5. D. Stutzbach, R. Rejaie, N. Duffield, S. Sen, and W. Willinger, "On Unbiased Sampling for Unstructured Peer-to-Peer Networks," IEEElACM Transactions on Networking, vol. 17, no. 02, pp. 377-390, 2009.
6. G. P. Jesi, A. Montresor, and M. van Steen, "Secure Peer Sampling," Computer Networks, vol. 54, no. 12, pp. 2086-2098, 2010.
7. D. Liu, P. Ning, and W. Du, "Detecting Malicious Beacon Nodes for Secure Location Discovery in Wireless Sensor Networks," in Proceedings of the 25th IEEE International Conference on Distributed Compltling Systems (ICDCS), 2005.
8. A. Singh, T-W. Ngan, P. Druschel, and D. S. Wallach, "Eclipse Attacks on Overlay Networks: Threats and Defenses," in Proc. of the 25th IEEE Inti Conference on Computer Communications (INFO COM), 2006.
9. J. Douceur and J. S. Donath, "The Sybil Attack," in Proceedings of the lrst International Workshop on Peer-to-Peer Systems (IPTPS), 2002, pp. 25 1-260.
10. E. Bortnikov, M. Gurevich, I. Keidar, G. Kliot, and A. Shraer, "Brahms: Byzantine Resilient Random Membership Sampling," Computer Networks, vol. 53, pp. 2340-2359, 2009.
11. E. Anceaume, Y. Busnel, and S. Gambs, "Uniform and Ergodic Sampling in Unstructured Peer-to-Peer Systems with Malicious Nodes," in Proceedings of the 14th International Conference On Principles Of Distributed Systems (OPODIS), vol. 6490, 2010, pp. 64-78.
12. Muthukrishnan, Data Streams: Algorithms and Applications. Now Publishers Inc., 2005.
13. Z. Bar-Yossef, T S. Jayram, R. Kumar, D. Sivakumar, and L. Trevisan, "Counting distinct elements in a data stream," in Proceedings of the 6th International Workshop on Randomization and Approximation Techniques (RANDOM). Springer-Verlag, 2002, pp. 1-10.
14. P. Flajolet and G. N. Martin, "Probabilistic counting algorithms for data base applications," Journal of Computer and System Sciences, vol. 3 1, no. 2, pp. 1 82-209, 1 985.
15. D. M. Kane, J. Nelson, and D. P. Woodruff, "An optimal algorithm for the distinct element problem," in Proceedings of the Symposium on Principles of Databases (PODS), 2010.
16. N. Alon, Y. Matias, and M. Szegedy, "The space complexity of approximating the frequency moments," in Proceedings of the twentyeighth annual ACM symposium on Theory of computing (STOC), 1 996, pp. 20-29.
17. M. Charikar, K. Chen, and M. Farach-Colton, "Finding frequent items in data streams," Theoretical Computer Science, vol. 3 1 2, no. I, pp. 3-15, 2004.
18. A. Chakrabarti, G. Cormode, and A. McGregor, "A near-optimal algorithm for computing the entropy of a stream," in In ACM-SIAM Symposium on Discrete Algorithms, 2007, pp. 328-335.
19. A. Lall, V. Sekar, M. Ogihara, J. Xu, and H. Zhang, "Data streaming algorithms for estimating entropy of network traffic," in Proceedings of the joint international conference on Measurement and modeling of computer systems (SIGMETRICS). ACM, 2006.
20. E. Anceaume and Y. Busnel, "An information divergence estimation over data streams," in Proceedings of the 11th IEEE International Symposium on Network Computing and Applications (NCA), 2012.
21. N. Lynch, Distributed Algorithms. Morgan Kaufmann Publishers, 1996.
22. P. B. Godfrey, S. Shenker, and I. Stoica, "Minimizing churn in distributed systems," in Proceedings of the ACM SIGCOMM, 2006.
23. G. Corm ode and S. Muthukrishnan, "An improved data stream summary: the count-min sketch and its applications," Journal of Algorithms, vol. 55, no. I, pp. 58-75, 2005.
24. T I. T Archive, ''http://ita.ee.lbl.gov/htmlltraces.html,'' Lawrence Berkeley National Laboratory, Apr. 2008.
25. S. Kullback and R. A. Leibler, "On information and sufficiency," The Annals of Mathematical Statistics, vol. 22, no. I, pp. 79-86, 1 95 1. [On line]. Available: http://dx.doi.orgll 0.2307/2236703
26. J. G. Keneny and J. L. Snell, Finite Markov Chains. Springer-v., 1 976.
27. G. Rubino and B. Sericola, "On weak lumpability in Markov chains," Journal of Applied Probability, vol. 26, 1 989.