V. Chandola, A. Banerjee, and V. Kumar, Anomaly detection, ACM Computing Surveys, vol.41, issue.3, pp.1-58, 2009.
DOI : 10.1145/1541880.1541882

B. K. Subhabrata, E. Krishnamurthy, S. Sen, Y. Zhang, and Y. Chen, Sketch-based change detection: Methods, evaluation, and applications, Internet Measurement Conference, pp.234-247, 2003.

V. Karamcheti, D. Geiger, Z. Kedem, and S. Muthuskrishnan, Detecting malicious network traffic using inverse distributions of packet contents, Proceeding of the 2005 ACM SIGCOMM workshop on Mining network data , MineNet '05, 2005.
DOI : 10.1145/1080173.1080176

A. Lakhina, M. Crovella, and C. Diot, Mining anomalies using traffic feature distributions, Proc. of the ACM SIGCOMM, 2005.

E. Anceaume, Y. Busnel, and S. Gambs, Uniform and Ergodic Sampling in Unstructured Peer-to-Peer Systems with Malicious Nodes, Proc. of the 14th international conference on Principles of distributed systems (OPODIS), pp.64-78, 2010.
DOI : 10.1007/11561071_71
URL : https://hal.archives-ouvertes.fr/hal-00554219

Z. Bar-yossef, T. S. Jayram, R. Kumar, D. Sivakumar, and L. Trevisan, Counting Distinct Elements in a Data Stream, Proc. of the 6th International Workshop on Randomization and Approximation Techniques (RANDOM), pp.1-10, 2002.
DOI : 10.1007/3-540-45726-7_1

P. Flajolet and G. N. Martin, Probabilistic counting algorithms for data base applications, Journal of Computer and System Sciences, vol.31, issue.2, pp.182-209, 1985.
DOI : 10.1016/0022-0000(85)90041-8
URL : https://hal.archives-ouvertes.fr/inria-00076244

D. M. Kane, J. Nelson, and D. P. Woodruff, An optimal algorithm for the distinct elements problem, Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems of data, PODS '10, 2010.
DOI : 10.1145/1807085.1807094

N. Alon, Y. Matias, and M. Szegedy, The space complexity of approximating the frequency moments, Proc. of the 28th annual ACM symposium on Theory of computing (STOC), pp.20-29, 1996.

M. Charikar, K. Chen, and M. Farach-colton, Finding frequent items in data streams, Theoretical Computer Science, vol.312, issue.1, pp.3-15, 2004.
DOI : 10.1016/S0304-3975(03)00400-6

A. Chakrabarti, G. Cormode, and A. Mcgregor, A near-optimal algorithm for computing the entropy of a stream, ACM-SIAM Symposium on Discrete Algorithms, pp.328-335, 2007.

A. Lall, V. Sekar, M. Ogihara, J. Xu, and H. Zhang, Data streaming algorithms for estimating entropy of network traffic, Proc. of the joint international conference on Measurement and modeling of computer systems (SIGMETRICS, 2006.

S. Guha, P. Indyk, and A. Mcgregor, Sketching information divergences Algorithms for distributed functional monitoring, Machine Learning Proc. of the 19th annual ACM- SIAM Symposium On Discrete Algorithms (SODA), pp.5-19, 2008.

C. Arackaparambil, J. Brody, and A. Chakrabarti, Functional Monitoring without Monotonicity, Proc. of the 36th ACM International Colloquium on Automata, Languages and Programming: Part 1, 2009.
DOI : 10.1007/978-3-642-02927-1_10

P. B. Gibbons and S. Tirthapura, Estimating simple functions on the union of data streams, Proceedings of the thirteenth annual ACM symposium on Parallel algorithms and architectures , SPAA '01, pp.281-291, 2001.
DOI : 10.1145/378580.378687

Z. Haung, K. Yi, and Q. Zhang, Randomized algorithms for tracking distributed count, frequencies, and ranks, Proceedings of the 31st symposium on Principles of Database Systems, PODS '12, 2012.
DOI : 10.1145/2213556.2213596

Z. Liu, B. Radunovic, and M. Vojnovic, Continuous distributed counting for non-monotonic streams, Proceedings of the 31st symposium on Principles of Database Systems, PODS '12, 2012.
DOI : 10.1145/2213556.2213597

E. Anceaume and Y. Busnel, An information divergence estimation over data streams, Proc. of the IEEE International Symposium on Network Computing and Applications (NCA), 2012.
URL : https://hal.archives-ouvertes.fr/hal-00725097

E. Anceaume, Y. Busnel, and S. Gambs, AnKLe: Detecting Attacks in Large Scale Systems via Information Divergence, 2012 Ninth European Dependable Computing Conference, 2012.
DOI : 10.1109/EDCC.2012.9
URL : https://hal.archives-ouvertes.fr/hal-00653240

T. Cover and J. Thomas, Elements of information theory, 1991.

E. Anceaume, Y. D. Busnel23-]-e, R. Demaine, J. I. Ortiz, and . Munro, A distributed information divergence estimation over data streams, " supplementary materials Frequency estimation of internet packet streams with limited space, Proceedings of the 10th Annual European Symposium on Algorithms, pp.348-360, 2002.

. Muthukrishnan, Data Streams: Algorithms and Applications, Foundations and Trends?? in Theoretical Computer Science, vol.1, issue.2, 2005.
DOI : 10.1561/0400000002

S. Kullback and R. A. Leibler, On Information and Sufficiency, The Annals of Mathematical Statistics, vol.22, issue.1, pp.79-86, 1951.
DOI : 10.1214/aoms/1177729694

S. M. Ali and S. D. Silvey, General Class of Coefficients of Divergence of One Distribution from Another, Journal of the Royal Statistical Society. Series B (Methodological), vol.28, issue.1, pp.131-142, 1966.

M. Durand and P. Flajolet, Log-log counting of large cardinalities, Proc. of the 11th European Symposium on Algorithms (ESA), 2003.

P. Gibbons, Data Streams Management: Processing High-Speed Data Streams, 2007.

J. Misra and D. Gries, Finding repeated elements, Science of Computer Programming, vol.2, issue.2, pp.143-152, 1982.
DOI : 10.1016/0167-6423(82)90012-0

E. Anceaume, Y. Busnel, and S. Gambs, Characterizing the adversarial power in uniform and ergodic node sampling, Proceedings of the First International Workshop on Algorithms and Models for Distributed Event Processing, AlMoDEP '11, 2011.
DOI : 10.1145/2031792.2031795
URL : https://hal.archives-ouvertes.fr/inria-00617866