مروری بر روش های تشخیص ناهنجاری مبتنی برگراف در شبکه های اجتماعی

Z. Papacharissi, “Community, and Culture on Social Network Sites,” A Networked Self: Identity, New York, Routledge, 2010.##

“Worldwide Social Networks Users,” eMarketer, 2017.##

X. Ying, X. Wu, and D. Barbara, “Spectrum based fraud detection in social networks,” IEEE 27^th International Conference of Data Engineering (ICDE), 2011.##

M. Fire, G. Katz, and Y. Elovici, “Strangers intrusion detection-detecting spammers and fake profiles in social networks based on topology anomalies,” ASE Human Journal, vol. 1, pp. 26-39, 2012.##

D. H. Chau, S. Pandit, and C. Faloutsos, “Detecting fraudulent personalities in networks of online auctioneers,” Knowledge Discovery in Databases: PKDD, 2006.##

D. Toshniwal and S.Yadav, “Adaptive Outlier Detection in Streaming Time Series,” International Conference on Asia Agriculture and Animal, 2011.##

V. Chandola, A. Banerjee, and V. Kumar, “Anomaly detection: A survey,” ACM Computing Surveys (CSUR), vol. 41, pp. 1-72, 2009.##

V. Barnett and T. Lewis, “Outliers in Statistical Data,” 3rd Edition, John Wiley & Sons, 1994.##

V. Hodge and J. Austin, “A survey of outlier detection methodologies,” Artificial Intelligence Review, vol. 22, pp. 85–126, 2004.##

V. Chandola, “Anomaly detection for symbolic sequences and time series data,” Ph.D. thesis, university of Minnesota, 2009.##

R. Hassanzadeh, R. Nayak, and D. Stebila, “ Analyzing the Effectivenees of Graph Metrics for Anomaly Detection in Online Social Networks,” Web Information Systems Engineering (WISE ), 2012.##

M. E. Newman, D. J. Watts, and S. H. Strogatz, “Random Graph Models of Social Networks,” National Academy of Sciences, vol. 99, pp. 2566-2572, 2002.##

R. Yu, X. He, and Y. Liu, “Glad: group anomaly detection in social media analysis,” ACM Transactions on Knowledge Discovery from Data (TKDD), 2015.##

Y. Chen and B. Malin, “Detection of anomalous insiders in collaborative environments via relational analysis of access logs,” 1^st ACM conference on Data and application security and privacy, 2011.##

Y. Chen, S. Nyemba, and B. Malin, “Auditing medical records accesses via healthcare interaction networks,” AMIA Annual Symposium Proceeding, 2012.##

Y. Chen, S. Nyemba, W. Zhang, and B. Malin, “Specializing network analysis to detect anomalous insider actions,” Security informatics, vol. 1, pp. 1-24, 2012.##

N. Jindal, B. Liu, and E. P. Lim, “Finding unusual review patterns using unexpected rules,” 19^th ACM international conference on Information and knowledge management, 2010.##

R. Kaur and S. Singh, “A survey of data mining and social network analysis based anomaly detection techniques,” Egyptian Informatics Journal, vol. 17, pp. 199-216, 2016.##

D. Savage, X. Zhang, X. Yu, P. Chou, and Q. Wan, “Anomaly detection in online social networks,” Social Networks, vol. 39, pp. 62-70, 2014.##

Z. Chen, W. Hendrix, and N. F. Samatova, “Community-based anomaly detection in evolutionary networks,” Intell. Inf. Syst., vol. 39, pp. 59-85, 2012.##

N. A. Heard, D. J. Weston, K. Platanioti, D. J. Hand, and others, “Bayesian anomaly detection methods for social networks,” The Annals of Applied Statistics, vol. 4, pp.    645–662, 2010.##

S. Pandit, D. Chau, S. Wang, and C. Faloutsos  “Netprobe, A fast and scalable system for fraud detection in online auction networks,” 16^th international conference on World Wide Web, 2007.##

L. Akoglu, M. McGlohon, and C. Faloutsos, “Anomaly Detection in Large Graphs,” School of Computer Science Carnegie Mellon University, 2009.##

F. Y. Edgeworth, “On discordant observations,” Philosophical Magazine, pp. 364-375, 1887.##

N. Shrivastava, A. Majumder, and R. Rastogi, “Mining (social) network graphs to detect random link attacks,” In Data Engineering, IEEE 24th International Conference on, 2008.##

L. Akoglu, M. McGlohon, and C. Faloutsos, “Oddball: spotting anomalies in weighted graphs,” Advances in Knowledge Discovery and Data Mining, 2010.##

M. A. Doostari, R. Zeinali, H. Lashkari, and M. Ajamzamani, “Anomaly Detection in Cliques of Online Social Networks Using Fuzzy Node-Fuzzy Graph,” Journal of Basic and Applied Scientific Research, vol. 3, pp. 614-626, 2013.##

R. Hassanzadeh and R. Nayak, “A semi-supervised         graph-based algorithm for detecting outliers in online-social-networks,” 28^th Annual ACM Symposium on Applied Computing, 2013.##

S. Y. Bhat and M. Abulaish, “Communities Against Deception in Online Social Networks,” Computer fraud Security, vol. 2, pp. 8-16, 2014.##

M. Abulaish and S. Y. Bhat, “A densitybased based approach to detect community evolutionary events in online social networks,” 12^th Social Network Analysis and Mining, 2013.##

D. Chakrabarti, “Autopart: parameter-free graph partitioning and outlier detection,” 8^th European Conference on Principles and Practice of Knowledge Discovery in Databases, 2004.##

X. Xu, N. Yuruk, Z. Feng, and T. A. Schweiger, “Scan: a structural clustering algorithm for networks,” 13^th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007.##

H. Sun, J. Huang, J. Han, H. Deng, and P. Zhao, “gskeletonclu: Density-based network clustering via structure-connected tree division or agglomeration,” 10^th IEEE International on DATA Mining, 2010.##

H. Tong and C. Y. Lin, “Non-Negative Residual Matrix Factorization with Application to Graph Anomaly Detection,”  11^th SIAM International Conference on Data Mining, 2011.##

B. Miller, N. Bliss, and P. J. Wolfe, “Subgraph detection using eigenvector L1 norms,” 24th Annual Conference on Neural Information Processing Systems, 2010.##

B. Miller, M. S. Beard, N. T. Bliss, and Others, “Eigenspace analysis for threat detection in social networks,” 14^th IEEE International Conference on Information Fusion, 2011.##

B. Miller, M. Beard, P. Wolfe, and N. Bliss, “A spectral framework for anomalous subgraph detection,” Signal Processing, IEEE Transactions, vol. 63, pp. 4191–4206, 2015.##

C. C. Noble and D. J. Cook, “Graph-based anomaly detection,” 9^th ACM SIGKDD international conference on Knowledge discovery and data mining, 2003.##

L. B. Holder, D. J. Cook, S. DjokO, et al, “Substucture Discovery in the SUBDUE System,” 3rd International Conference on Knowledge Discovery and Data Mining, 1994.##

W. Eberle and L. Holder, “Anomaly detection in data represented as graphs,” Intelligent Data Analysis, vol. 11, pp. 663–689, 2007.##

M. Davis, W. Liu, P. Miller, and G. Redpath, “Detecting Anomalies in Graphs with Numeric Labels,” 20^th ACM International Conference on Information and Knowledge Management, 2011.##

M. Gupta, A. Mallya, S. Roy, J. Cho, and J. Han, “Local learning for mining outlier subgraphs from network datasets,” SIAM International Conference on Data Mining, 2014.##

J. Li, H. Dani, X. Hu, and H. Liu, “Radar: Residual Analysis for Anomaly Detection in Attributed Networks,” 26^th International Joint Conference on Artificial Intelligence, 2017.##

X. Hu, J. Tang, Y. Zhang, and H. Liu, “Social Spammer Detection in Microblogging,” 23^th International Joint Conference on Artificial Intelligence, 2013.##

X. He, D. Cai and P. Niyogi, “Laplacian Score for Feature Selection,” 18^th International Conference on Neural Information Processing Systems, 2005.##

L. Ghanoui, G. Li, V. Duong, V. Pham, and Srivasta, “Sparse machine learning methods for understanding large text corpora,” Conference on Intelligent Data Understanding, 2011.##

J. Gao, F. Liang, W. Fan, C. Wang, and Y. Sun, “On community outliers and their efficient detection in information networks,” 16^th ACM SIGKDD international conference on Knowledge discovery and data mining, 2010.##

T. Ji, J. Gao, and D. Yang, “A Scalable Algorithm for Detecting Community Outliers in Social Networks,” International Conference on Web-Age Information Management, 2012.##

E. Müller, P. I. Sánchez , Y. Mülle, and K. Böhm, “Ranking outlier nodes in subspaces of attributed graphs,” 29^th  International Conference on Data Engineering Workshops, 2013.##

P. I. Sánchez, E. Müller, F. Laforet, and F. Keller, “Statistical Selection of Congruent Subspaces for Mining Attributed Graphs,” 13^th IEEE International Conference on Data Mining, 2013.##

P. I. Sánchez, E. Müller, O. Irmler, and K. Böhm, “Local context selection for outlier ranking in graphs with multiple numeric node attributes,” 26^th International Conference on Scientific and Statistical Database Management, 2014.##

W. Yang, G. W. Shen, W. Wang, L. Y. Gong, and M. Yu, “Anomaly detection in microblogging via co-clustering,” Journal of Computer Science and Technology, vol. 30, pp. 1097–1108, 2015.##

M. A. Prado-Romero and A. Gago-Alonso, “Community Feature Selection for Anomaly Detection in Attributed Graphs,” Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2017.##

V. D. Blondel, J. Guillaume, R. Lambiotte, and Lef, “Fast unfolding of communities in large networks,” Journal of Statistical Mechanics: Theory and Experiment, vol. 2008, 2008.##

L. Akoglu and C. Faloutsos, “Event detection in time series of mobile communication graphs,” Army Science Conference, 2010.##

D. Koutra, E. E. Papalexakis, and C. Faloutsos, “Tensorsplat: Spotting latent anomalies in time,” 16^th IEEE Panhellenic Conference on Informatics, 2012.##

W. Yu, C. C. Aggarwal, S. Ma, and h. Wang, “On anomalous hotspot discovery in graph streams,” 13^th IEEE International Conference on Data Mining, 2013.##

M. Gupta, J. Gao, Y. Sun, and J. Han, “Integrating community matching and outlier detection for mining evolutionary community outliers,” 18^th international conference on Knowledge discovery and data mining, 2012.##

T. Ji, D. Yang, and J. Gao, “Incremental local evolutionary outlier detection for dynamic social networks,” 13^th European Conference on Machine Learning and Knowledge Discovery in Databases, 2013.##

M. Mongiovi, P. Bogdanov, R. Ranca, E. E. Papalexakis, C. Faloutsos, and A. K. Singh, “Netspot: Spotting significant anomalous regions on dynamic networks,” SIAM International Conference on Data Mining, 2013.##

Z. Huang and D. D. Zeng, “A link prediction approach to anomalous email detection,” International Conference on  Systems, Man and Cybernetics, 2006.##

B. Thompson and T. Eliassi-Rad, “Discovery and analysis of patterns and anomalies in volatile time-evolving networks 1^st  Workshop on Information in Networks,” 2009.##

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

E. E. Papalexakis, C. Faloutsos, and N. Sidiropoulos, “Parcube: Sparse parallelizable tensor decompositions,” Machine Learning and Knowledge Discovery in Databases, 2012.

Y. Yasami and F. Safaei, “A statistical infinite feature cascade-based approach to anomaly detection for dynamic social networks,” Computer Communications, vol. 100, pp. 52-64, 2017.

J. Van Gae, L. J. The, and Z. Ghahramani, “The infinite factorial hidden Markov model,”  23^rd  Annual Conference on Neural Information Processing Systems, 2009.

P. V. Bindu and T. Santhi, “Mining Social Networks for Anomalies: Methods and Challenges,” Journal of Network and Computer Applications, vol. 68, pp. 213-229, 2016.

X. H. Dang, I. Assent, R. T. Ng, A. ZimekSchub, and Schub, “Discriminative features for identifying and interpreting outliers,” 30^th IEEE International Conference on Data Engineering, 2014.