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2013 | 1 | 63--66
Tytuł artykułu

Usage of RBF Networks in prediction of network traffic

Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Prediction of future time series values is area of statistics and computer science research related to pattern recognition. Especially possibility of prediction of the future computer network traffic may be usable in detection of abnormal situations like DoS attacks or occurrence of problems with network infrastructure. The article is devoted to usage artificial neural networks, with radial basis activation function for prediction of network traffic in sample local area networks.(original abstract)
Rocznik
Tom
1
Strony
63--66
Opis fizyczny
Twórcy
autor
  • Telekomunikacja Polska S.A.
autor
  • Lodz University of Technology, Poland
autor
  • Telekomunikacja Polska S.A.
Bibliografia
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  • ITU-T E.507 Models for Forecasting International Traffic, ITU 1998, http://www.itu.int/rec/T-REC-E.507-198811-I/en
  • ITU-T Recommendation E.490.1: Overview of Recommendations on traffic engineering, ITU 2003, http://www.itu.int/rec/T-REC-E.490.1-200301-I/en
  • Jǎek R., Szmit A., Szmit M.: Usage of Modern Exponential-Smoothing Models in Network Traffic Modelling, Advances in Intelligent Systems and Computing Volume 210, 2013, pp. 435-444 (Nostradamus 2013: Prediction, Modeling and Analysis of Complex Systems), DOI:978-3-319-00542-3_43
  • Liu, W; Lin S., Piegorsch W. W.: Construction of Exact Simultaneous Confidence Bands for a Simple Linear Regression Model, International Statistical Review 76 (1): 39-57.doi:10.1111/j.1751-5823.2007.00027.x.
  • Markou M., Singh S.: Novelty detection: a review part 1: statistical approaches, Signal Processing, vol. 83, pp. 2481 - 2497, Decemeber 2003;
  • M̈nz G.: Traffic Anomaly Detection and Cause Identification Using Flow-Level Meas- urements, TUM, M̈chen 2010, http://www.net.in.tum.de/fileadmin/TUM/NET/NET- 2010-06-1.pdf
  • Quittek J., Zseby T., Claise B., Zander S.: Requirements for IP Flow Information Export (IPFIX), RFC 3917, Network Working Group 2004
  • Rajahalme J., Conta A., Carpenter B., Deering S.: IPv6 Flow Label Specification, RFC 3697, Network Working Group 2004
  • Rousseeuw P. J., Leroy A. M.: Robust Regression and Outlier Detection, Wiley, 1987
  • Siris V.A., Papaglou F., "Application of anomaly detection algorithms for detecting syn floodinfg attacks," in Proceedings of the IEEE Global Telecommunications Conference, vol. 4, pp. 2050-2054, 2004
  • Szmit A., Szmit M.: O wykorzystaniu modeli ekonometrycznych do prognozowania modeli ruchu sieciowego, Zeszyty Naukowe Organizacja i Zarządzanie Nr 1154 (55), Politechnika Łódzka, Łódź 2013, pp. 193-201, ISSN: 0137-2599
  • Szmit M., Adamus S., Bugała S., Szmit A.: Implementation of Brutlag's algorithm in Anomaly Detection 3.0, Federated Conference on Computer Science and Information Systems, Proceedings of the Federated Conference on Computer Science and Information Systems, pp. 685-691, PTI, IEEE, Wrocław 2011
  • Szmit M., Szmit A., Adamus S., Bugała S.: Usage of Holt-Winters Model and Multilayer Perceptron in Network Traffic Modelling and Anomaly Detection, Informatica Vol. 36, Nr 4, pp. 359-368
  • Szmit M., Szmit A.: Usage of Modified Holt-Winters Method in the Anomaly Detection of Network Traffic: Case Studies, Journal of Computer Networks and Communications, vol. 2012, DOI:10.1155/2012
  • Szmit M., Szmit A.: Usage of Pseudo-estimator LAD and SARIMA Models for Network Traffic Prediction. Case Studies, Communications in Computer and Information Science, 2012, Volume 291, 229-236, DOI: 10.1007/978-3-642-31217-5_25
  • Szmit M., Szmit A.: Use of Holt-Winters method in the analysis of network traffic. Case study, Springer Communications in Computer and Information Science vol. 160, 18th Conference Computer Networks, 2011, s. 224-231, ISSN: 1865-0929; ISBN: 978-3-642-21770-8, DOI: 10.1007/978-3-642-21771-5_24
  • Szmit M.: Vyǔit́ nula-jednǐkov́ch model̊ pro behavioŕlń anaĺzuś̌ov́ho provozu, Internet, competitiveness and organizational security, TBU, Zĺn 2011
  • Vala R., Malanik D., Jǎek, R. "Usability of Software Intrusion-Detection System in Web Applications", Advances in Intelligent Systems and Computing, Vol. 189, pp. 159-166, Springer-Verlag, Berlin 2013
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Typ dokumentu
Bibliografia
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Identyfikator YADDA
bwmeta1.element.ekon-element-000171278673

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