Usage of Modern Exponential-Smoothing Models in Network Traffic Modelling

The article summarized current state of our works regarding usage of exponential smoothing Holt-Winters’ based models for analysis, modelling and forecasting Time Series with data of computer network traffic. Especially we use two models proposed by J. W. Taylor to deal with double and triple seasonal cycles for modelling network traffic in two local area networks and three campus networks. We use three time series with data of TCP, UDP and ICMP traffic (given by number of packets per interval) on each network.

[1]  Francesco Palmieri,et al.  Network anomaly detection through nonlinear analysis , 2010, Comput. Secur..

[2]  Peter J. Rousseeuw,et al.  Robust regression and outlier detection , 1987 .

[3]  James W. Taylor.  Exponentially weighted methods for forecasting intraday time series with multiple seasonal cycles , 2010 .

[4]  Tomás Cipra,et al.  Exponential smoothing for time series with outliers , 2011, Kybernetika.

[5]  Daniel A. Keim,et al.  Business Process Impact Visualization and Anomaly Detection , 2006, Inf. Vis..

[6]  Ehud Rivlin,et al.  ROR: rejection of outliers by rotations in stereo matching , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[7]  Maciej Szmit,et al.  Implementation of Brutlag's algorithm in Anomaly Detection 3.0 , 2012, 2012 Federated Conference on Computer Science and Information Systems (FedCSIS).

[8]  V. Yohai,et al.  Robust Statistics: Theory and Methods , 2006 .

[9]  Louis Kratz,et al.  Anomaly detection in extremely crowded scenes using spatio-temporal motion pattern models , 2009, CVPR.

[10]  Maciej Szmit,et al.  Usage of Holt-Winters Model and Multilayer Perceptron in Network Traffic Modelling and Anomaly Detection , 2012, Informatica.

[11]  Juan M. Corchado,et al.  Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living, 10th International Work-Conference on Artificial Neural Networks, IWANN 2009 Workshops, Salamanca, Spain, June 10-12, 2009. Proceedings, Part II , 2009, IWANN.

[12]  Yun Wang,et al.  Statistical Techniques for Network Security: Modern Statistically-Based Intrusion Detection and Protection , 2008 .

[13]  Maciej Szmit,et al.  Usage of Modified Holt-Winters Method in the Anomaly Detection of Network Traffic: Case Studies , 2012, J. Comput. Networks Commun..

[14]  Gerhard Münz,et al.  Traffic anomaly detection and cause identification using flow-level measurements , 2010 .

[15]  Christophe Croux,et al.  Robust Forecasting with Exponential and Holt-Winters Smoothing , 2007 .

[16]  Mooi Choo Chuah,et al.  ECG Anomaly Detection via Time Series Analysis , 2007, ISPA Workshops.

[17]  J. W. Taylor,et al.  Short-term electricity demand forecasting using double seasonal exponential smoothing , 2003, J. Oper. Res. Soc..

[18]  Paul Goodwin,et al.  The Holt-Winters Approach to Exponential Smoothing: 50 Years Old and Going Strong , 2010 .

[19]  Ruppa K. Thulasiram,et al.  Proceedings of the SSDSN, UPWN, WISH, SGC, ParDMCom, HiPCoMB, and IST-AWSN international workshops held at ISPA 2007 on Frontiers of High Performance Computing and Networking , 2007, HiPC 2007.

[20]  Álvaro Herrero,et al.  International Joint Conference CISIS'12-ICEUTE'12-SOCO'12 Special Sessions, Ostrava, Czech Republic, September 5th-7th, 2012 , 2013, CISIS/ICEUTE/SOCO Special Sessions.

[21]  Galit Shmueli,et al.  Automated time series forecasting for biosurveillance , 2007, Statistics in medicine.

[22]  Milos Hauskrecht,et al.  Evidence-based Anomaly Detection in Clinical Domains , 2007, AMIA.

[23]  Hans-Peter Kriegel,et al.  LOF: identifying density-based local outliers , 2000, SIGMOD 2000.

[24]  Wei Liu,et al.  Construction of Exact Simultaneous Confidence Bands for a Simple Linear Regression Model , 2008 .

[25]  Michael J. Black,et al.  Robust principal component analysis for computer vision , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[26]  Tomás Hanzák.  Holt-Winters method with general seasonality , 2012, Kybernetika.

[27]  Xu Zhi-gao.  Regression Forecast and Abnormal Data Detection Based on Support Vector Regression , 2009 .

[28]  Maciej Szmit,et al.  Usage of Pseudo-estimator LAD and SARIMA Models for Network Traffic Prediction: Case Studies , 2012, CN.

[29]  Peter J. Rousseeuw,et al.  Robust Regression and Outlier Detection , 2005, Wiley Series in Probability and Statistics.

[30]  Sameer Singh,et al.  Novelty detection: a review - part 1: statistical approaches , 2003, Signal Process..

[31]  Bohdan Macukow,et al.  Heat Consumption Prediction with Multiple Hybrid Models , 2009, IWANN.

[32]  Maciej Szmit,et al.  Use of Holt-Winters Method in the Analysis of Network Traffic: Case Study , 2011, CN.

[33]  Raymond T. Ng,et al.  Distance-based outliers: algorithms and applications , 2000, The VLDB Journal.

[34]  Jake D. Brutlag,et al.  Aberrant Behavior Detection in Time Series for Network Monitoring , 2000, LISA.

[35]  Roman Jasek,et al.  Usability of Software Intrusion-Detection System in Web Applications , 2012, CISIS/ICEUTE/SOCO Special Sessions.

[36]  Pascal Bondon,et al.  Robust estimation of SARIMA models: Application to short-term load forecasting , 2009, 2009 IEEE/SP 15th Workshop on Statistical Signal Processing.