DocumentCode :
661236
Title :
Time Series Forecasting Methods for Creating Digital Signature of Network Segments Using Flow Analysis
Author :
Oliveira de Assis, Marcos Vinicius ; Zacaron, Alexandro Marcelo ; Lemes Proenca, Mario
Author_Institution :
Comput. Sci. Dept., State Univ. of Londrina Londrina, Londrina, Brazil
fYear :
2012
fDate :
12-16 Nov. 2012
Firstpage :
161
Lastpage :
170
Abstract :
This paper presents the use of two methods for creating a digital signature of a network segment based on flow analysis (DSNSF), which can be defined as a traffic characterization of a network segment. This characterization is achieved through the statistical forecasting method Holt-Winters. Furthermore, a modification is proposed to this traditional method aiming towards better results in its use for creating DSNSF. The data used in the tests are flows collected through NetFlow v9. The results demonstrate that the proposed amendment on the Holt-Winters method showed better results creating DSNSF than the traditional method.
Keywords :
digital signatures; network theory (graphs); statistical analysis; time series; DSNSF; Holt-Winters statistical forecasting method; NetFlow v9; digital signature of a network segment based on flow analysis; time series forecasting methods; Algorithm design and analysis; Complexity theory; Digital signatures; Forecasting; Market research; Smoothing methods; Time series analysis; Baseline; DSNSF; Holt-Winters; NetFlow;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Chilean Computer Science Society (SCCC), 2012 31st International Conference of the
Conference_Location :
Valparaiso
ISSN :
1522-4902
Print_ISBN :
978-1-4799-2937-5
Type :
conf
DOI :
10.1109/SCCC.2012.26
Filename :
6694086
Link To Document :
بازگشت