Anomaly Detection Using Forecasting Methods ARIMA and HWDS

Proceedings - International Conference of the Chilean Computer Science Society, SCCC

Volumn 0, Issue , 2013, Pages 63-66

  Pena, Eduardo H M ^a   De Assis, Marcos V O ^a   Proença, Mario Lemes ^a  

^a STATE UNIVERSITY OF LONDRINA   (Brazil)

Author keywords

anomaly detection; arima; hwds

Indexed keywords

COMPUTER SCIENCE; COMPUTERS;

ARIMA; AUTOREGRESSIVE INTEGRATED MOVING AVERAGE MODELS; EARLY WARNING SYSTEM; FORECASTING METHODS; HOLT-WINTERS METHOD; HWDS; PREDICTIVE CAPABILITIES; TRAFFIC CHARACTERIZATION;

ANOMALY DETECTION;

EID: 85011851545     PISSN: 15224902     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SCCC.2013.18     Document Type: Conference Paper

References (19)

1. A. Lakhina, M. Crovella, and C. Diot, "Characterization of networkwide anomalies in traffic flows," in Proceedings of the 4th ACM SIGCOMM conference on Internet measurement ser. IMC '04. New York, NY, USA: ACM, 2004, pp. 201-206. [Online]. Available: http://doi.acm.org/10.1145/1028788.1028813
2. G. E. P. Box and G. M. Jenkins, Time Series Analysis: Forecasting and Control 3rd ed. Upper Saddle River, NJ, USA: Prentice Hall PTR, 1994.
3. M. V. O. Assis, A. Zacaron, and M. Proenca, "Time series forecasting methods for creating digital signature of network segment using flow analysis," in 31th International Conference of Chilean Computer Science Society, 2012. SCCC'12. 2012.
4. F. Guo, Y. Yang, and L. Duan, "Anomaly detection by clustering in the network," in Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on 2009, pp. 1-4.
5. Q. Quan, C. Hong-Yi, and Z. Rui, "Entropy based method for network anomaly detection," in Proceedings of the 2009 15th IEEE Pacific Rim International Symposium on Dependable Computing ser. PRDC '09. Washington, DC, USA: IEEE Computer Society, 2009, pp. 189-191. [Online]. Available: http://dx.doi.org/10.1109/PRDC.2009.38
6. S. Novakov, C.-H. Lung, I. Lambadaris, and N. Seddigh, "Studies in applying PCA and wavelet algorithms for network traffic anomaly detection," in High Performance Switching and Routing (HPSR), 2013 IEEE 14th International Conference on 2013, pp. 185-190.
7. T.-R. Li and W. ming Pan, "Intrusion detection system based on new association rule mining model," in Granular Computing, 2005 IEEE International Conference on vol. 2, 2005, pp. 512-515 Vol. 2.
8. M. Thottan and J. Chuanyi, "Anomaly detection in IP networks," Signal Processing, IEEE Transactions on vol. 51, no. 8, pp. 2191-2204, 2003.
9. B. Krishnamurthy, S. Sen, Y. Zhang, and Y. Chen, "Sketch-based change detection: methods, evaluation, and applications," in Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement ser. IMC '03. New York, NY, USA: ACM, 2003, pp. 234-247.
10. B. Zhu and S. Sastry, "Revisit dynamic arima based anomaly detection," in Privacy, security, risk and trust (passat), 2011 ieee third international conference on social computing (socialcom) 2011, pp. 1263-1268.
11. A. Yaacob, I. K. T. Tan, S. F. Chien, and H. K. Tan, "Arima based network anomaly detection," in Communication Software and Networks, 2010. ICCSN '10. Second International Conference on 2010, pp. 205-209.
12. J. D. Brutlag, "Aberrant behavior detection in time series for network monitoring," in Proceedings of the 14th USENIX Conference on System Administration ser. LISA '00. Berkeley, CA, USA: USENIX Association, 2000, pp. 139-146. [Online]. Available: http://dl.acm.org/citation.cfm?id=1045502.1045530
13. S. Chang, X. Qiu, Z. Gao, F. Qi, and K. Liu, "A flow-based anomaly detection method using entropy and multiple traffic features," in Broadband Network and Multimedia Technology (IC-BNMT), 2010 3rd IEEE International Conference on Oct 2010, pp. 223-227.
14. J. D. Brutlag, "Aberrant Behavior Detection in Time Series for Network Monitoring," Proceedings of the 14th Systems Administration Conference (LISA 2000) Dec. 2000.
15. M. V. de Assis, L. Carvalho, J. Rodrigues, and M. J. L. Proença, "Holtwinters statistical forecasting and ACO metaheuristic for traffic characterization," in 2013 IEEE International Conference on Communications (ICC) June 2013, pp. 2524-2528.
16. M. Proenca, B. Zarpelao, and L. Mendes, "Anomaly detection for network servers using digital signature of network segment," in Telecommunications, 2005. advanced industrial conference on telecommunications. aict 2005. proceedings 2005, pp. 290-295.
17. B. B. Zarpelão, L. D. S. Mendes, and M. L. Proença, Jr., "Anomaly detection aiming pro-active management of computer network based on digital signature of network segment," J. Netw. Syst. Manage. vol. 15, no. 2, pp. 267-283, Jun. 2007.
18. A. A. Amaral, B. B. Zarpelão, L. de Souza Mendes, J. J. P. C. Rodrigues, and M. L. P. Junior, "Inference of network anomaly propagation using spatio-temporal correlation," Journal of Network and Computer Applications vol. 35, no. 6, pp. 1781-1792, 2012.
19. B. Zarpelao, L. Mendes, M. Proenca, and J. Rodrigues, "Parameterized anomaly detection system with automatic configuration," in Global Telecommunications Conference, 2009. GLOBECOM 2009. IEEE Nov 2009, pp. 1-6.