A family of joint sparse PCA algorithms for anomaly localization in network data streams

IEEE Transactions on Knowledge and Data Engineering

Volumn 25, Issue 11, 2013, Pages 2421-2433

  Jiang, Ruoyi ^a,b   Fei, Hongliang ^b,c   Huan, Jun ^b  

^a Adometry Corp   (United States)

^b University of Kansas   (United States)

^c IBM T J WATSON RESEARCH CENTER   (United States)

Author keywords

Anomaly detection; anomaly localization; joint sparsity; network data stream; optimization; PCA

Indexed keywords

ANOMALY DETECTION; ANOMALY LOCALIZATIONS; JOINT SPARSITY; NETWORK DATA; PCA;

OPTIMIZATION; PRINCIPAL COMPONENT ANALYSIS; VIRTUAL REALITY;

DATA COMMUNICATION SYSTEMS;

EID: 84884780968     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2012.176     Document Type: Article

References (43)

1. S. Budhaditya, D.-S. Pham, M. Lazarescu, and S. Venkatesh, "Effective Anomaly Detection in Sensor Networks Data Streams," Proc. IEEE Int'l Conf. Data Mining (ICDM '09), pp. 722-727, 2009.
2. M. Isaac, B. Raul, E. Gerard, and G. Moisès, "On-Line Fault Diagnosis Based on the Identification of Transient Stages," Proc. 20th European Symp. Computer Aided Process Eng., 2010.
3. J. Silva and R. Willett, "Detection of Anomalous Meetings in a Social Network," Proc. 42nd Ann. Conf. Information Sciences and Systems (CISS '08), pp. 636-641, 2008.
4. J. Zhang, Q. Gao, and H. Wang, "Anomaly Detection in High-Dimensional Network Data Streams: A Case Study," Proc. IEEE Int'l Conf. Intelligence and Security Informatics, pp. 251-253, June 2008.
5. H. Nguyen, Y. Tan, and X. Gu, "PAL: Propagation-Aware Anomaly Localization for Cloud Hosted Distributed Applications," Proc. Managing Large-Scale Systems via the Analysis of System Logs and the Application of Machine Learning Techniques, 2011.
6. N. Xu et al., "A Wireless Sensor Network for Structural Monitoring," Proc. Int'l Conf. Embedded Networked Sensor Systems, pp. 13-24, 2004. (Pubitemid 41563345)
7. C. Franke and M. Gertz, "Orden: Outlier Region Detection and Exploration in Sensor Networks," Proc. ACM SIGMOD Int'l Conf. Management of Data, pp. 1075-1078, 2009.
8. X. Liu, X. Wu, H. Wang, R. Zhang, J. Bailey, and K. Ramamohanarao, "Mining Distribution Change in Stock Order Streams," Proc. Int'l Conf. Data Eng. (ICDE), pp. 105-108, 2010.
9. A. Lakhina, M. Crovella, and C. Diot, "Diagnosing Network-Wide Traffic Anomalies," Proc. ACM SIGCOMM, pp. 219-230, 2004. (Pubitemid 40954882)
10. L. Huang, M.I. Jordan, A. Joseph, M. Garofalakis, and N. Taft, "In-Network PCA and Anomaly Detection," Proc. Advances in Neural Information Processing System (NIPS), pp. 617-624, 2006.
11. A. Lakhina, M. Crovella, and C. Diot, "Mining Anomalies Using Traffic Feature Distributions," Proc. ACM SIGCOMM, pp. 217-228, 2005. (Pubitemid 46323506)
12. H. Ringberg, A. Soule, J. Rexford, and C. Diot, "Sensitivity of PCA for Traffic Anomaly Detection," SIGMETRICS '07: Proc. ACM SIGMETRICS Int'l Conf. Measurement and Modeling of Computer Systems, pp. 109-120, 2007. (Pubitemid 350158077)
13. H. Zou, T. Hastie, and R. Tibshirani, "Sparse Principal Component Analysis," J. Computational and Graphical Statistics, vol. 15, no. 2, pp. 265-286, 2006. (Pubitemid 43935978)
14. D. Brauckhoff, K. Salamatian, and M. May, "Applying PCA for Traffic Anomaly Detection: Problems and Solutions," Proc. IEEE INFOCOM, pp. 2866-2870, 2009.
15. X. Gu and H. Wang, "Online Anomaly Prediction for Robust Cluster Systems," Proc. Int'l Conf. Data Eng. (ICDE), pp. 1000-1011, 2009.
16. J.-G. Lee, J. Han, and X. Li, "Trajectory Outlier Detection: A Partition-and-Detect Framework," Proc. Int'l Conf. Data Eng. (ICDE), pp. 140-149, 2008.
17. D. Brauckhoff, X. Dimitropoulos, A. Wagner, and K. Salamatian, "Anomaly Extraction in Backbone Networks Using Association Rules," Proc. Ninth ACM SIGCOMM Conf. Internet Measurement Conf., pp. 28-34, 2009.
18. E. Keogh, J. Lin, and A. Fu, "Hot Sax: Efficiently Finding the Most Unusual Time Series Subsequence," Proc. Fifth IEEE Int'l Conf. Data Mining, pp. 226-233, 2005. (Pubitemid 47385697)
19. J.B. Tenenbaum, V. de Silva, and J.C. Langford, "A Global Geometric Framework for Nonlinear Dimensionality Reduction," Science, vol. 290, no. 5500, pp. 2319-2323, 2000. (Pubitemid 32041577)
20. A. Lung-Yut-Fong, C. Lévy-Leduc, and O. Cappé, "Distributed Detection/Localization of Change-Points in High-Dimensional Network Traffic Data," Statistics and Computing, vol. 22, pp. 485-496, 2009.
21. T. Idé, A.C. Lozano, N. Abe, and Y. Liu, "Proximity-Based Anomaly Detection Using Sparse Structure Learning," Proc. SIAM Int'l Conf. Data Mining, pp. 97-108, 2009.
22. T. Idé, S. Papadimitriou, and M. Vlachos, "Computing Correlation Anomaly Scores Using Stochastic Nearest Neighbors," ICDM '07: Proc. Seventh IEEE Int'l Conf. Data Mining, pp. 523-528, 2007.
23. S. Hirose, K. Yamanishi, T. Nakata, and R. Fujimaki, "Network Anomaly Detection Based on Eigen Equation Compression," KDD '09: Proc. 15th ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining, pp. 1185-1194, 2009.
24. J. Zhang, Q. Gao, H.H. Wang, Q. Liu, and K. Xu, "Detecting Projected Outliers in High-Dimensional Data Streams," Proc. Int'l Conf. Database and Expert Systems Applications, pp. 629-644, 2009.
25. S. Yang and W. Zhou, "Anomaly Detection on Collective Moving Patterns: Manifold Learning Based Analysis of Traffic Streams," Proc. IEEE Third Int'l Conf. Social Computing (socialcom), pp. 704-707, 2011.
26. H. Cao, Y. Zhou, L. Shou, and G. Chen, "Attribute Outlier Detection over Data Streams," Proc. Int'l Conf. Database Systems for Advanced Applications, vol. 2, pp. 216-230, 2010.
27. R. Jiang, H. Fei, and J. Huan, "Anomaly Localization by Joint Sparse PCA in Wireless Sensor Networks," Proc. Fourth Int'l Workshop Knowledge Discovery from Sensor Data, 2010.
28. R. Jiang, H. Fei, and J. Huan, "Anomaly Localization for Network Data Streams with Graph Joint Sparse PCA," Proc. ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining (KDD), pp. 886-894, 2011.
29. P.H. dos Santos Teixeira and R.L. Milidiú , "Data Stream Anomaly Detection through Principal Subspace Tracking," SAC '10: Proc. ACM Symp. Applied Computing, pp. 1609-1616, 2010.
30. M. Yuan, M. Yuan, Y. Lin, and Y. Lin, "Model Selection and Estimation in Regression with Grouped Variables," J. Royal Statistical Soc., Series B, vol. 68, pp. 49-67, 2006. (Pubitemid 43415335)
31. H. Zou and T. Hastie, "Regularization and Variable Selection via the Elastic Net," J. Royal Statistical Soc. B, vol. 67, pp. 301-320, 2005. (Pubitemid 40465877)
32. R. Jenatton, G. Obozinski, and F. Bach, "Structured Sparse Principal Component Analysis," Proc. 13th Int'l Conf. Artificial Intelligence and Statistics (AISTATS), 2010.
33. H. Fei and J. Huan, "Boosting with Structure Information in the Functional Space: An Application to Graph Classification," Proc. ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining (SIGKDD), 2010.
34. Y. Nesterov, Introductory Lectures on Convex Optimization: A Basic Course. Springer, 2003.
35. S. Boyd and L. Vandenberghe, Convex Optimization. Cambridge Univ. Press, 2004.
36. C.-T. Chu, S.K. Kim, Y.-A. Lin, Y. Yu, G.R. Bradski, A.Y. Ng, and K. Olukotun, "Map-Reduce for Machine Learning on Multicore," Proc. Advances in Neural Information Processing System (NIPS), pp. 281-288, 2006.
37. D.P. Bertsekas, Nonlinear Programming, second ed. Athena Scientific, 1999.
38. V. Chandola, A. Banerjee, and V. Kumar, "Anomaly Detection: A Survey," ACM Computing Survey, vol. 41, no. 3, article 15, 2009.
39. E. Keogh and T. Folias, "The UCR Time Series Data Mining Archive," http://www.cs.ucr.edu/eamonn/TSDMA/index.html, 2002.
40. A. Frank and A. Asuncion, "UCI Machine Learning Repository," http://archive.ics.uci.edu/ml, 2010.
41. H.G. Kayacik, A.N. Zincir-Heywood, and M.I. Heywood, "Selecting Features for Intrusion Detection: A Feature Relevance Analysis on KDD 99," Proc. Third Ann. Conf. Privacy, Security and Trust (PST), 2005.
42. S. Mukkamala and A.H. Sung, "Feature Ranking and Selection for Intrusion Detection Systems Using Support Vector Machines," Proc. Second Digital Forensic Research Workshop, 2002.
43. S. Mukkamala and A.H. Sung, "Feature Selection for Intrusion Detection Using Neural Networks and Support Vector Machines," J. Transportation Research Board of the Nat'l Academies, 2003.