E. Anceaume, F. Brasileiro, R. Ludinard, and A. Ravoaja, Peercube : A hypercube-based p2p overlay robust against collusion and churn Gudmundsson : Detecting Single File Movement, Proceedings of the IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO Proceedings of the 16th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pp.15-24, 2008.

[. Bezdek, R. Ehrlich, and W. , FCM: The fuzzy c-means clustering algorithm, Computers & Geosciences, vol.10, issue.2-3, pp.191-203, 1984.
DOI : 10.1016/0098-3004(84)90020-7

J. [. Benkert, F. Gudmundsson, T. Hübner, and . Wolle, Reporting flock patterns, Proceedings of the 14th European Symposium on Algorithms, pp.660-671, 2006.

J. [. Benkert, F. Gudmundsson, T. Hübner, and . Wolle, Reporting flock patterns, Computational Geometry, vol.41, issue.3, pp.111-125, 2008.
DOI : 10.1016/j.comgeo.2007.10.003

URL : http://doi.org/10.1016/j.comgeo.2007.10.003

H. [. Beckmann, R. Kriegel, and . Schneider, Seeger : The R*tree : An Efficient and Robust Access Method for Points and Rectangles, Proceedings of the ACM SIGMOD International Conference on Management of Data, pp.322-331, 1990.

F. [. Choffnes, Z. Bustamante, and . Ge, Crowdsourcing Servicelevel Network Event Monitoring, Proceedings of the ACM SIGCOMM Conference, pp.387-398, 2010.

M. Correia, N. Ferreira-neves, P. P. Veríssimodlr77-]-a, N. M. Dempster, D. B. Laird et al., How to Tolerate Half Less One Byzantine Nodes in Practical Distributed Systems Choffnes : Service-Level Network Event Detection from Edge Systems [Def77] D. Defays : An efficient algorithm for a complete link method, Proceedings of the 23rd International Symposium on Reliable Distributed Systems, SRDS Thèse de doctorat Maximum Likelihood from Incomplete Data via the EM Algorithm, pp.174-183364, 1977.

M. Ester, H. P. Kriegel, J. Sander, and X. Xu, A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise, Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining, KDD Saia et M. Young : Making Chord Robust to Byzantine Attacks. Dans Proceedings of the 13rd European Symposium on Algorithms, pp.226-231, 1996.

C. Y. Hong, M. Caesar, N. Duffield, J. A. Wanghw79-]-j, M. A. Hartigan et al., Tiresias : Online Anomaly Detection for Hierarchical Operational Network Data Hamerly et C. Elkan : Alternatives to the K-means Algorithm That Find Better Clusterings Algorithm AS 136 : A K-Means Clustering Algorithm, Proceedings of the 32nd IEEE International Conference on Distributed Computing Systems, ICDCS Proceedings of the 11th International Conference on Information and Knowledge Management, CIKMJLO07] C. S. Jensen, D. Lin et Beng-Chin O. : Continuous Clustering of Moving Objects. Knowledge and Data Engineering, pp.173-182, 1979.

M. L. Yiu, X. Zhou, C. S. Jensen, and H. T. Shen, Discovery of Convoys in Trajectory Databases, Proceedings VLDB Endowment, vol.1, issue.1, pp.1068-1080, 2008.

R. Kotla, L. Alvisi, M. Dahlin, A. Clement, and E. Wong, Zyzzyva : Speculative Byzantine Fault Tolerance : A New Approach to Linear Filtering and Prediction Problems, Proceedings of the 21st ACM SIGOPS Symposium on Operating Systems Principles, SOSP, pp.45-5835, 1960.

. Travaux-connexes-[-kr87-]-l, P. Kaufman, and . Rousseeuw, Clustering by Means of Medoids, 1987.

S. [. Locher, R. Schmid, and . Wattenhofer, eQuus: A Provably Robust and Locality-Aware Peer-to-Peer System, Sixth IEEE International Conference on Peer-to-Peer Computing (P2P'06), pp.3-11, 2006.
DOI : 10.1109/P2P.2006.17

S. [. Malgorzata, Adarshpal : A survey of fault localization techniques in computer networks, Science of Computer Programming, vol.53, issue.2, pp.165-194, 2004.

M. L. Massie, B. N. Chun, and D. E. Culler, The ganglia distributed monitoring system: design, implementation, and experience, Parallel Computing, vol.30, issue.7, 2003.
DOI : 10.1016/j.parco.2004.04.001

. [. Maymounkov, Mazì eres : Kademlia : A Peer-to-Peer Information System Based on the XOR Metric, Revised Papers from the First International Workshop on Peer-to-Peer Systems, IPTPS, pp.53-65, 2002.

A. [. Pelleg and . Moore, X-means : Extending K-means with Efficient Estimation of the Number of Clusters, Proceedings of the 17th International Conference on Machine Learning, pp.727-734, 2000.

V. [. Park and . Pai, CoMon, ACM SIGOPS Operating Systems Review, vol.40, issue.1, pp.65-74, 2006.
DOI : 10.1145/1113361.1113374

P. [. Rowstron and . Druschel, Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems, Proceedings of the IFIP/ACM International Conference on Distributed Systems Platforms, Middleware, pp.329-350, 2001.
DOI : 10.1007/3-540-45518-3_18

P. S. Ratnasamy, M. Francis, R. Handley, S. Karp, and . Shenker, A Scalable Content-addressable Network, Proceedings of the Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications, SIGCOMM, pp.161-172, 2001.

J. Sander, M. Ester, H. P. Kriegel, and X. Xu, Density-Based Clustering in Spatial Databases : The Algorithm GDBSCAN and Its Applications, Data Mining and Knowledge Discovery, vol.2, issue.2, pp.169-194, 1998.
DOI : 10.1023/A:1009745219419

]. R. Sib73 and . Sibson, SLINK : an optimally efficient algorithm for the single-link cluster method, The Computer Journal, vol.16, issue.1, pp.30-34, 1973.

. Smk-+-01-]-i, R. Stoica, D. Morris, M. F. Karger, H. Kaashoek et al., Chord : A Scalable Peer-to-peer Lookup Service for Internet Applications, SIGCOMM Computer Communication Review, vol.31, issue.4, pp.149-160, 2001.

. R. Vbt09-]-m, P. Vieira, and V. J. Bakalov, Tsotras : On-line Discovery of Flock Patterns in Spatio-temporal Data, Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS, pp.286-295, 2009.

K. [. Van-renesse, W. Birman, and . Vogels, Astrolabe, ACM Transactions on Computer Systems, vol.21, issue.2, pp.164-206, 2003.
DOI : 10.1145/762483.762485

H. Yan, A. Flavel, Z. Ge, A. Gerber, D. Massey et al., Argus: End-to-end service anomaly detection and localization from an ISP's point of view, 2012 Proceedings IEEE INFOCOM, pp.2756-2760, 2012.
DOI : 10.1109/INFCOM.2012.6195694

Z. Tan, X. Gong, and M. Gu, Wamboldt : Self-correlating Predictive Information Tracking for Large-scale Production Systems, Proceedings of the 6th International Conference on Autonomic Computing, ICAC, pp.33-42, 2009.

. Fixme-la-forte-présence, Le second niveau quantà quantà lui organise les entités présentes dans une même région de l'espace au sein d'une DHT PeerCube, Les propriétés combinées de ces deux niveaux permettent ainsi d'obtenir une structure auto-organisante et tolérante au dynamisme des entités du système. La recherche de ces entités aux perceptions similaires permet ainsi d'appliquer le modèle et les algorithmes décrits dans le chapitre 3

. [. Bibliographie, F. Anceaume, R. Brasileiro, and . Ludinard, Ravoaja : Peercube : A hypercube-based p2p overlay robust against collusion and churn, Proceedings of the IEEE International Conference on Self-Adaptive and Self- Organizing Systems, SASO, pp.15-24, 2008.

]. E. Anceaume, E. Le-merrer, R. Ludinard, B. Sericola, and G. Straub, FixMe: A Self-organizing Isolated Anomaly Detection Architecture for Large Scale Distributed Systems, Proceedings of the 16th International Conference On Principles Of Distributed Systems, OPODIS, pp.1-12, 2012.
DOI : 10.1007/978-3-642-35476-2_1

URL : https://hal.archives-ouvertes.fr/hal-00736922

E. E. Anceaume, R. Le-merrer, B. Ludinard, G. Sericola, and . Straub, FixMe : Détection Répartie de Défaillances Isolées, 15èmes Rencontres Francophones sur les Aspects Algorithmiques des Télécommunications, AlgoTel, pp.1-4, 2013.

P. [. Eastlake and . Jones, Rapport technique, IETF, US Secure Hash Algorithm, vol.1, issue.SHA1, 2001.

M. [. Hartigan and . Wong, Algorithm AS 136: A K-Means Clustering Algorithm, Applied Statistics, vol.28, issue.1, pp.100-108, 1979.
DOI : 10.2307/2346830

S. [. Locher, R. Schmid, and . Wattenhofer, eQuus: A Provably Robust and Locality-Aware Peer-to-Peer System, Sixth IEEE International Conference on Peer-to-Peer Computing (P2P'06), pp.3-11, 2006.
DOI : 10.1109/P2P.2006.17

P. S. Ratnasamy, M. Francis, R. Handley, S. Karp, and . Shenker, A Scalable Content-addressable Network, Proceedings of the Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications, SIGCOMM, pp.161-172, 2001.

. Smk-+-01-]-i, R. Stoica, D. Morris, M. F. Karger, H. Kaashoek et al., Chord : A Scalable Peer-to-peer Lookup Service for Internet Applications, SIGCOMM Computer Communication Review, vol.31, issue.4, pp.149-160, 2001.

. Considérons-une-cellule-de-fixme, et supposons qu'elle est peuplée de h ? n entitésentitésà l'instant k. Ces h entités s'organisent alors au sein d'une instance PeerCube

J. [. Mills, J. Martin, W. Burbank, and . Kasch, Protocol and Algorithms Specification, Network Time Protocol Version, vol.4, 2010.

B. [. Rubino and . Sericola, Sojourn times in finite Markov processes, Journal of Applied Probability, vol.35, issue.04, pp.744-756, 1989.
DOI : 10.1017/S0021900200027613

URL : https://hal.archives-ouvertes.fr/inria-00075739

M. Srivatsa and L. Liu, Vulnerabilities and Security Threats in Structured Peer-to-Peer Systems : A quantitiative Analysis, Proceedings of the 20th Annual Computer Security Applications Conference, 2004.

M. [. Saad and . Schultz, Topological properties of hypercubes, IEEE Transactions on Computers, vol.37, issue.7, 1988.
DOI : 10.1109/12.2234

D. Cependant-ces-identifiantsàidentifiantsà-validité-limitée-induisent-un-churn-supplémentaire-dans-la, Nous avonsétudiéavonsétudié l'impact des identifiantsàidentifiantsà validité limitée sur la dynamique du système. Nous avons montré que l'impact de cette technique reste négligeable vis` a-vis des du churn naturel dans le système. Enfin, nous avonsétudiéavonsétudié l'impact de la présence d'entités malveillantes dans le système sur les opérations de recherche lookup

. [. Bibliographie, F. Anceaume, R. Brasileiro, and . Ludinard, Ravoaja : Peercube : A hypercube-based p2p overlay robust against collusion and churn, Proceedings of the IEEE International Conference on Self-Adaptive and Self- Organizing Systems, SASO, pp.15-24, 2008.

F. [. Anceaume, R. Castella, and . Ludinard, Markov Chains Competing for Transitions: Application to Large-Scale Distributed Systems, Methodology and Computing in Applied Probability, vol.15, issue.2, pp.305-332, 2013.
DOI : 10.1007/s11009-011-9239-6

URL : https://hal.archives-ouvertes.fr/inria-00485667

E. Anceaume and R. Ludinard, Performance evaluation of large-scale dynamic systems, ACM SIGMETRICS Performance Evaluation Review, vol.39, issue.4, pp.108-117, 2012.
DOI : 10.1145/2185395.2185447

URL : https://hal.archives-ouvertes.fr/hal-00653409

B. [. Anceaume, R. Sericola, and . Ludinard, Tronel : Modeling and Evaluating Targeted Attacks in Large Scale Dynamic Systems, Proceedings of the 41rst International Conference on Dependable Systems and Networks, DSN, pp.347-358, 2011.
DOI : 10.1109/dsn.2011.5958248

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.395.7367

M. Srivatsa and L. Liu, Vulnerabilities and Security Threats in Structured Peer-to-Peer Systems : A quantitiative Analysis, Proceedings of the 20th Annual Computer Security Applications Conference, 2004.

M. [. Saad and . Schultz, Topological properties of hypercubes, Proceedings of the IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO, pp.15-24, 1988.
DOI : 10.1109/12.2234

F. [. Anceaume, R. Castella, and . Ludinard, Markov Chains Competing for Transitions: Application to Large-Scale Distributed Systems, Methodology and Computing in Applied Probability, vol.15, issue.2, pp.305-332, 2013.
DOI : 10.1007/s11009-011-9239-6

URL : https://hal.archives-ouvertes.fr/inria-00485667

]. E. Anceaume, E. Le-merrer, R. Ludinard, B. Sericola, and G. Straub, FixMe: A Self-organizing Isolated Anomaly Detection Architecture for Large Scale Distributed Systems, Proceedings of the 16th International Conference On Principles Of Distributed Systems, OPODIS, pp.1-12, 2012.
DOI : 10.1007/978-3-642-35476-2_1

URL : https://hal.archives-ouvertes.fr/hal-00736922

R. [. Anceaume and . Ludinard, Performance evaluation of large-scale dynamic systems, ACM SIGMETRICS Performance Evaluation Review, vol.39, issue.4, pp.108-117, 2012.
DOI : 10.1145/2185395.2185447

URL : https://hal.archives-ouvertes.fr/hal-00653409

B. [. Anceaume, R. Sericola, and . Ludinard, Tronel : Modeling and Evaluating Targeted Attacks in Large Scale Dynamic Systems, Proceedings of the 41rst International Conference on Dependable Systems and Networks, DSN, pp.347-358, 2011.

H. [. Breunig, R. T. Kriegel, J. Ng, and . Sander, LOF : Identifying Density-based Local Outliers, Proceedings of the ACM SIG- MOD International Conference on Management of Data, pp.93-104, 2000.

M. Ester, H. P. Kriegel, J. Sander, and X. Xu, A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise, Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining, KDD, pp.226-231, 1996.

R. [. Ge, B. Collins, and . Ruback, Automatically detecting the small group structure of a crowd, 2009 Workshop on Applications of Computer Vision (WACV), pp.1-8, 2009.
DOI : 10.1109/WACV.2009.5403123

S. [. Solera and . Calderara, Social Groups Detection in Crowd through Shape-Augmented Structured Learning, Image Analysis and Processing ? ICIAP 2013, pp.542-551, 2013.
DOI : 10.1007/978-3-642-41181-6_55

D. [. Sochman and . Hogg, Who knows who - Inverting the Social Force Model for finding groups, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), pp.830-837, 2011.
DOI : 10.1109/ICCVW.2011.6130338

A. Kermarrec, E. Le-merrer, N. L. Scouarnec, R. Ludinard, P. Maillé et al., Performance evaluation of a peer-to-peer backup system using buffering at the edge, Computer Communications, vol.52, 2014.
DOI : 10.1016/j.comcom.2014.06.002

URL : https://hal.archives-ouvertes.fr/hal-01185286

R. Ludinard, E. Totel, F. Tronel, V. Nicomette, M. Kaaniche et al., An Invariant-Based Approach for Detecting Attacks Against Data in Web Applications, International Journal of Secure Software Engineering, vol.5, issue.1, 2014.
DOI : 10.4018/ijsse.2014010102

URL : https://hal.archives-ouvertes.fr/hal-01083296

E. Anceaume, F. Castella, R. Ludinard, and B. Sericola, Markov Chains Competing for Transitions: Application to Large-Scale Distributed Systems, Methodology and Computing in Applied Probability, vol.15, issue.2, pp.305-332, 2013.
DOI : 10.1007/s11009-011-9239-6

URL : https://hal.archives-ouvertes.fr/inria-00485667

E. Anceaume, R. Ludinard, and B. Sericola, Performance evaluation of large-scale dynamic systems, ACM SIGMETRICS Performance Evaluation Review, vol.39, issue.4, pp.108-117, 2012.
DOI : 10.1145/2185395.2185447

URL : https://hal.archives-ouvertes.fr/hal-00653409

E. Anceaume, F. Brasileiro, R. Ludinard, B. Sericola, and F. Tronel, DEPENDABILITY EVALUATION OF CLUSTER-BASED DISTRIBUTED SYSTEMS, International Journal of Foundations of Computer Science, vol.22, issue.05, pp.1123-1142, 2011.
DOI : 10.1142/S0129054111008593

URL : https://hal.archives-ouvertes.fr/hal-00650086

E. Anceaume, Y. Busnel, E. Le-merrer, R. Ludinard, J. Marchand et al., Anomaly Characterization in Large Scale Networks, 2014 44th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, 2014.
DOI : 10.1109/DSN.2014.23

URL : https://hal.archives-ouvertes.fr/hal-00948135

E. Anceaume, E. Le-merrer, R. Ludinard, B. Sericola, and E. G. Straub, FixMe: A Self-organizing Isolated Anomaly Detection Architecture for Large Scale Distributed Systems, Proceedings of the 16th International Conference On Principles Of Distributed Systems, OPODIS, pp.1-15, 2012.
DOI : 10.1007/978-3-642-35476-2_1

URL : https://hal.archives-ouvertes.fr/hal-00736922

R. Ludinard, E. Totel, F. Tronel, V. Nicomette, M. Kaaniche et al., Detecting attacks against data in web applications, 2012 7th International Conference on Risks and Security of Internet and Systems (CRiSIS), pp.1-8, 2012.
DOI : 10.1109/CRISIS.2012.6378943

URL : https://hal.archives-ouvertes.fr/hal-00735997

E. Anceaume, B. Sericola, R. Ludinard, and F. Tronel, Modeling and evaluating targeted attacks in large scale dynamic systems, 2011 IEEE/IFIP 41st International Conference on Dependable Systems & Networks (DSN), pp.347-358, 2011.
DOI : 10.1109/DSN.2011.5958248

URL : https://hal.archives-ouvertes.fr/hal-00650095

E. Anceaume, R. Ludinard, and B. Sericola, Analytic Study of the Impact of Churn in Cluster-Based Structured P2P Overlays, 2010 IEEE International Conference on Communications, pp.302-307, 2010.
DOI : 10.1109/ICC.2010.5501827

URL : https://hal.archives-ouvertes.fr/hal-00476330

E. Anceaume, F. Brasiliero, R. Ludinard, B. Sericola, and F. Tronel, Brief Announcement: Induced Churn to Face Adversarial Behavior in Peer-to-Peer Systems, Proceedings of the 11th International Symposium on Stabilization, Safety et Security of Distributed Systems, SSS, pp.773-774, 2009.
DOI : 10.1007/978-3-642-05118-0_54

URL : https://hal.archives-ouvertes.fr/hal-00420559

E. Anceaume, F. Brasileiro, R. Ludinard, and A. Ravoaja, PeerCube: A Hypercube-Based P2P Overlay Robust against Collusion and Churn, 2008 Second IEEE International Conference on Self-Adaptive and Self-Organizing Systems, pp.15-24, 2008.
DOI : 10.1109/SASO.2008.44

E. Anceaume, Y. Busnel, E. Le-merrer, R. Ludinard, J. Marchand et al., Anomaly characterization problems, 16èmes Rencontres Francophones sur les Aspects Algorithmiques des Télécommunications, AlgoTel, pp.1-4, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00985641

E. Anceaume, E. Le-merrer, R. Ludinard, B. Sericola, and G. Straub, A Self-organising Isolated Anomaly Detection Architecture for Large Scale Systems, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00907374

E. Anceaume, E. Le-merrer, R. Ludinard, B. Sericola, and G. Straub, FixMe : détection répartie de défaillances isolées, 15èmes Rencontres Francophones sur les Aspects Algorithmiques des Télécommunications, AlgoTel, pp.1-4, 2013.

R. Ludinard, L. L. Hennaff, and E. Totel, RRABIDS, un système de détection d'intrusion pour les applications Ruby on Rails, Actes du Symposium 2011 sur la Sécurité des Technologies de l'Information et des Communications, 2011.

E. Anceaume, R. Ludinard, B. Sericola, and F. Tronel, Modélisation etÉvaluation et´etÉvaluation des Attaques Ciblées dans un Overlay Structuré, Colloque Francophone sur l Ingénierie des Protocoles, CFIP, 2011.

E. Anceaume, R. Ludinard, F. Tronel, F. Brasiliero, and B. Sericola, Analytical Study of Adversarial Strategies in Cluster-based Overlays, 2009 International Conference on Parallel and Distributed Computing, Applications and Technologies, pp.293-298, 0199.
DOI : 10.1109/PDCAT.2009.62

URL : https://hal.archives-ouvertes.fr/hal-00408871

E. , L. Merrer, R. Ludinard, B. Sericola, and G. Straub, Method for isolated anomaly detection in large-scale audio/video/data processing systems, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00914908

E. , L. Merrer, R. Ludinard, B. Sericola, and G. Straub, Method for isolated anomaly detection in large-scale data processing systems, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00914908

M. M. Breunig, H. P. Kriegel, and J. Sander, OPTICS : Ordering Points To Identify the Clustering Structure, Liste des publications Références Proceedings of the ACM SIGMOD International Conference on Management of Data, pp.49-60, 1999.

F. E. Anceaume, R. Brasiliero, B. Ludinard, F. Sericola, and . Tronel, Brief Announcement: Induced Churn to Face Adversarial Behavior in Peer-to-Peer Systems, Proceedings of the 11th International Symposium on Stabilization, Safety, and Security of Distributed Systems, SSS, pp.773-774, 2009.
DOI : 10.1007/978-3-642-05118-0_54

URL : https://hal.archives-ouvertes.fr/hal-00420559

F. E. Anceaume, R. Brasiliero, B. Ludinard, F. Sericola, and . Tronel, DEPENDABILITY EVALUATION OF CLUSTER-BASED DISTRIBUTED SYSTEMS, International Journal of Foundations of Computer Science, vol.22, issue.05, pp.1123-1142, 2011.
DOI : 10.1142/S0129054111008593

URL : https://hal.archives-ouvertes.fr/hal-00650086

. Abl-+-14a-]-e, Y. Anceaume, E. Busnel, R. Le-merrer, J. Ludinard et al., Anomaly Characterization in Large Scale Networks, Proceedings of the 44th International Conference on Dependable Systems and Networks, DSN, 2014.

Y. E. Anceaume, E. Busnel, R. Le-merrer, J. Ludinard, B. Marchand et al., Anomaly Characterization Problems, 16èmes Rencontres Francophones sur les Aspects Algorithmiques des Télécommunications, AlgoTel, pp.1-4, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00985641

F. [. Anceaume, R. Brasileiro, and . Ludinard, Ravoaja : Peercube : A hypercube-based p2p overlay robust against collusion and churn, Proceedings of the IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO, pp.15-24, 2008.

F. [. Anceaume, R. Castella, and . Ludinard, Markov Chains Competing for Transitions: Application to Large-Scale Distributed Systems, Methodology and Computing in Applied Probability, vol.15, issue.2, pp.305-332, 2013.
DOI : 10.1007/s11009-011-9239-6

URL : https://hal.archives-ouvertes.fr/inria-00485667

E. E. Anceaume, R. Le-merrer, B. Ludinard, G. Sericola, and . Straub, FixMe: A Self-organizing Isolated Anomaly Detection Architecture for Large Scale Distributed Systems, Proceedings of the 16th 201
DOI : 10.1007/978-3-642-35476-2_1

URL : https://hal.archives-ouvertes.fr/hal-00736922

E. E. Anceaume, R. Le-merrer, B. Ludinard, G. Sericola, and . Straub, A Self-organising Isolated Anomaly Detection Architecture for Large Scale Systems, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00907374

J. [. Avizienis, B. Laprie, C. Randell, and . Landwehr, Basic concepts and taxonomy of dependable and secure computing, IEEE Transactions on Dependable and Secure Computing, vol.1, issue.1, pp.11-33, 2004.
DOI : 10.1109/TDSC.2004.2

R. [. Anceaume, B. Ludinard, and . Sericola, Analytic Study of the Impact of Churn in Cluster-Based Structured P2P Overlays, 2010 IEEE International Conference on Communications, pp.302-307, 2010.
DOI : 10.1109/ICC.2010.5501827

URL : https://hal.archives-ouvertes.fr/hal-00476330

R. [. Anceaume and . Ludinard, Performance evaluation of large-scale dynamic systems, ACM SIGMETRICS Performance Evaluation Review, vol.39, issue.4, pp.108-117, 2012.
DOI : 10.1145/2185395.2185447

URL : https://hal.archives-ouvertes.fr/hal-00653409

R. E. Anceaume, F. Ludinard, F. Tronel, and . Brasiliero, Sericola : Analytical Study of Adversarial Strategies in Cluster-based Overlays, Proceedings of the 2nd International Workshop on Reliability, Availability, and Security, WRAS, pp.293-298, 2009.

[. Arcep, Haut et très haut débit sur réseaux fixes au 30 septembre 2013

C. [. Awerbuch, Scheideler : Towards Scalable and Robust Overay Networks, Proceedings of the International Workshop on Peer-to- Peer Systems, IPTPS, 2007.

B. [. Anceaume, R. Sericola, and . Ludinard, Tronel : Modeling and Evaluating Targeted Attacks in Large Scale Dynamic Systems, Proceedings of the 41rst International Conference on Dependable Systems and Networks, DSN, pp.347-358, 2011.

M. [. Buchin, J. Buchin, and . Gudmundsson, Detecting single file movement, Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems, GIS '08, pp.1-10, 2008.
DOI : 10.1145/1463434.1463476

B. , J. Bezdek, R. Ehrlich, and W. , Full : FCM : The Fuzzy C-Means Clustering Algorithm, Références 203 [, pp.191-203, 1984.

J. [. Benkert, F. Gudmundsson, T. Hübner, and . Wolle, Reporting flock patterns, Proceedings of the 14th European Symposium on Algorithms, pp.660-671, 2006.
DOI : 10.1016/j.comgeo.2007.10.003

URL : http://doi.org/10.1016/j.comgeo.2007.10.003

J. [. Benkert, F. Gudmundsson, T. Hübner, and . Wolle, Reporting flock patterns, Computational Geometry, vol.41, issue.3, pp.111-125, 2008.
DOI : 10.1016/j.comgeo.2007.10.003

URL : http://doi.org/10.1016/j.comgeo.2007.10.003

H. [. Breunig, R. T. Kriegel, J. Ng, and . Sander, LOF : Identifying Density-based Local Outliers, Proceedings of the ACM SIG- MOD International Conference on Management of Data, pp.93-104, 2000.
DOI : 10.1007/978-3-540-48247-5_28

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.18.7553

H. [. Beckmann, R. Kriegel, and . Schneider, Seeger : The R*tree : An Efficient and Robust Access Method for Points and Rectangles, Proceedings of the ACM SIGMOD International Conference on Management of Data, pp.322-331, 1990.

F. [. Choffnes, Z. Bustamante, and . Ge, Crowdsourcing Servicelevel Network Event Monitoring, Proceedings of the ACM SIGCOMM Conference, pp.387-398, 2010.
DOI : 10.1145/1851182.1851228

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.373.2623

N. [. Correia, P. Ferreira-neves, and . Veríssimo, How to tolerate half less one Byzantine nodes in practical distributed systems, Proceedings of the 23rd IEEE International Symposium on Reliable Distributed Systems, 2004., pp.174-183, 2004.
DOI : 10.1109/RELDIS.2004.1353018

J. D. Case, M. Fedor, M. L. Schoffstall, and J. Davin, Simple Network Management Protocol (SNMP) Rapport technique, IETF, 1990.

]. D. Cho10, Choffnes : Service-Level Network Event Detection from Edge Systems, Thèse de doctorat, 2010.

N. [. Dempster and D. B. Laird, Rubin : Maximum Likelihood from Incomplete Data via the EM Algorithm, Journal of the Royal Statistical Society : Series B, vol.39, pp.1-38, 1977.

P. [. Eastlake and . Jones, Rapport technique, IETF, US Secure Hash Algorithm, vol.1, issue.SHA1, 2001.

M. Ester, H. P. Kriegel, J. Sander, and X. Xu, A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise, Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining, KDD, pp.226-231, 1996.

R. Fiat, J. Saia, M. Younggcr09, ]. W. Ge, and R. T. Collins, Making Chord Robust to Byzantine Attacks Ruback : Automatically detecting the small group structure of a crowd, Proceedings of the 13rd European Symposium on Algorithms IEEE Workshop on Applications of Computer Vision, WACV, pp.803-814, 2005.

C. Y. Hong, M. Caesar, N. Duffield, J. Wanghe02-]-g, C. Hamerly et al., Tiresias : Online Anomaly Detection for Hierarchical Operational Network Data Alternatives to the K-means Algorithm That Find Better Clusterings Holt : Forecasting seasonals and trends by exponentially weighted moving averages : Algorithm AS 136 : A K-Means Clustering Algorithm, Proceedings of the 11th International Conference on Information and Knowledge Management, CIKMJLO07] C. S. Jensen, D. Lin et Beng-Chin O. : Continuous Clustering of Moving Objects. Knowledge and Data Engineering, pp.173-182, 1979.

M. L. Yiu, X. Zhou, C. S. Jensen, and H. T. Shen, Discovery of Convoys in Trajectory Databases, Proceedings VLDB Endowment, vol.1, issue.1, pp.1068-1080, 2008.

R. Kotla, L. Alvisi, M. Dahlin, A. Clement, E. E. Wongkal60-]-r et al., Zyzzyva : Speculative Byzantine Fault Tolerance A New Approach to Linear Filtering and Prediction Problems Van Kempen : Performance evaluation of a peer-to-peer backup system using buffering at the edge, Proceedings of the 21st ACM SIGOPS Symposium on Operating Systems Principles, SOSP, pp.45-5835, 1960.

L. [. Ludinard and E. Hennaff, Totel : RRABIDS, un système de détection d'intrusion pour les applications Ruby on Rails, Actes du Symposium 2011 sur la Sécurité des Technologies de l'Information et des Communications, 2011.

[. Merrer, R. Ludinard, B. Sericola, and G. Straub, Method for Isolated Anomaly Detection in Large-scale Data Processing Systems, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00914908

[. Merrer, R. Ludinard, B. Sericola, and G. Straub, Method for Isolated Anomaly Detection in Large-scale Audio/Video/Data Processing Systems, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00914908

S. [. Locher, R. Schmid, and . Wattenhofer, eQuus: A Provably Robust and Locality-Aware Peer-to-Peer System, Sixth IEEE International Conference on Peer-to-Peer Computing (P2P'06), pp.3-11, 2006.
DOI : 10.1109/P2P.2006.17

. Ltt-+-12-]-r, E. Ludinard, F. Totel, V. Tronel, M. Nicomette et al., Detecting Attacks Against Data in Web Applications, Proceedings of the 7th International Conference on Risks and Security of Internet and Systems, pp.1-8, 2012.

E. R. Ludinard, F. Totel, V. Tronel, M. Nicomette, E. Kaaniche et al., Bachy : An Invariant-based Approach for Detecting Attacks against Data in Web Applications, International Journal of Secure Software Engineering (IJSSE)

S. [. Malgorzata, Adarshpal : A survey of fault localization techniques in computer networks, Science of Computer Programming, vol.53, issue.2, pp.165-194, 2004.

M. L. Massie, B. N. Chun, and D. E. Culler, The ganglia distributed monitoring system: design, implementation, and experience, Parallel Computing, vol.30, issue.7, 2003.
DOI : 10.1016/j.parco.2004.04.001

. [. Maymounkov, Mazì eres : Kademlia : A Peer-to-Peer Information System Based on the XOR Metric, Revised Papers from the First International Workshop on Peer-to-Peer Systems, IPTPS, pp.53-65, 2002.

J. [. Mills, J. Martin, W. Burbank, and . Kasch, Protocol and Algorithms Specification, Network Time Protocol Version, vol.4, 2010.

]. E. Pag54 and . Page, Continuous Inspection Schemes, Biometrika, vol.41, issue.12, pp.100-115, 1954.

R. Pelleg and A. Moore, X-means : Extending K-means with Efficient Estimation of the Number of Clusters, Proceedings of the 17th International Conference on Machine Learning, pp.727-734, 2000.

V. [. Park and . Pai, CoMon, ACM SIGOPS Operating Systems Review, vol.40, issue.1, pp.65-74, 2006.
DOI : 10.1145/1113361.1113374

P. [. Rowstron and . Druschel, Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems, Proceedings of the IFIP/ACM International Conference on Distributed Systems Platforms, Middleware, pp.329-350, 2001.
DOI : 10.1007/3-540-45518-3_18

P. S. Ratnasamy, M. Francis, R. Handley, S. Karp, and . Shenker, A Scalable Content-addressable Network, Proceedings of the Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications, SIGCOMM, pp.161-172, 2001.

]. R. Riv92 and . Rivest, The MD5 Message-Digest Algorithm. Rapport technique, IETF, 1992.

B. [. Rubino and . Sericola, Sojourn times in finite Markov processes, Journal of Applied Probability, vol.35, issue.04, pp.744-756, 1989.
DOI : 10.1017/S0021900200027613

URL : https://hal.archives-ouvertes.fr/inria-00075739

S. [. Solera and . Calderara, Social Groups Detection in Crowd through Shape-Augmented Structured Learning, Image Analysis and Processing ? ICIAP 2013, pp.542-551, 2013.
DOI : 10.1007/978-3-642-41181-6_55

J. Sander, M. Ester, H. P. Kriegel, and X. Xu, Density-Based Clustering in Spatial Databases : The Algorithm GDBSCAN and Its Applications, Data Mining and Knowledge Discovery, vol.2, issue.2, pp.169-194, 1998.
DOI : 10.1023/A:1009745219419

D. [. Sochman and . Hogg, Who knows who - Inverting the Social Force Model for finding groups, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), pp.830-837, 2011.
DOI : 10.1109/ICCVW.2011.6130338

]. R. Sib73 and . Sibson, SLINK : an optimally efficient algorithm for the single-link cluster method, The Computer Journal, vol.16, issue.1, pp.30-34, 1973.

M. Srivatsa and L. Liu, Vulnerabilities and Security Threats in Structured Peer-to-Peer Systems : A quantitiative Analysis, Proceedings of the 20th Annual Computer Security Applications Conference, 2004.

. Smk-+-01-]-i, R. Stoica, D. Morris, M. F. Karger, H. Kaashoek et al., Chord : A Scalable Peer-to-peer Lookup Service for Internet Applications, SIGCOMM Computer Communication Review, vol.31, issue.4, pp.149-160, 2001.

M. Saad and . Schultz, Topological properties of hypercubes, IEEE Transactions on Computers, vol.37, issue.7, 1988.
DOI : 10.1109/12.2234

. R. Vbt09-]-m, P. Vieira, and V. J. Bakalov, Tsotras : On-line Discovery of Flock Patterns in Spatio-temporal Data, Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS, pp.286-295, 2009.

K. [. Van-renesse, W. Birman, and . Vogels, Astrolabe, ACM Transactions on Computer Systems, vol.21, issue.2, pp.164-206, 2003.
DOI : 10.1145/762483.762485

]. P. Win60 and . Winters, Forecasting Sales by Exponentially Weighted Moving Averages, Management Science, vol.6, pp.324-342, 1960.

H. Yan, A. Flavel, Z. Ge, A. Gerber, D. Massey et al., Argus: End-to-end service anomaly detection and localization from an ISP's point of view, 2012 Proceedings IEEE INFOCOM, pp.2756-2760, 2012.
DOI : 10.1109/INFCOM.2012.6195694

Z. Tan, X. Gong, and M. Gu, Wamboldt : Self-correlating Predictive Information Tracking for Large-scale Production Systems, Proceedings of the 6th International Conference on Autonomic Computing, ICAC, pp.33-42, 2009.

>. Pr{?-n and =. , Relation (7.6)) en fonction de m, ? pour P ?=1 dans le cas, p.174

>. Pr{?-n and =. , Relation (7.6)) en fonction de m, ? pour les deux distributions initiales ? (1) et ? (2) pour P ?=1 dans le cas o` u ? = 4096, p.175

D. Chemins-indépendants, 011, p.182