An Abnormal IP Traffic Detection Model Based on Scale-Free Network

Jun Li; Yan Niu

doi:10.4028/www.scientific.net/AMM.44-47.849

Paper Titles

Study on Reliability Test Methods of Machining Center
p.829

Reliability Test Design for Five-Axis Machining Center
p.834

Design and Implementation of WSN Visualized Management System
p.839

WSN Networking Protocol Based on Dynamic Changing Channel
p.844

An Abnormal IP Traffic Detection Model Based on Scale-Free Network
p.849

Optical Fiber Temperature Measurement Technique Based on Fluorescence Mechanism
p.854

Study on System of 3D Virtual NC Machining Environment
p.859

Hand-Eye Calibration of Machine Vision System for Manipulator
p.864

Yield Management with SD Model Based on Customer Lifetime Value in Semiconductor Industry
p.869

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 44-47An Abnormal IP Traffic Detection Model Based on...

An Abnormal IP Traffic Detection Model Based on Scale-Free Network

Abstract:

A model of detecting an abnormal IP traffic in a subset of network is described. The model is based on the hypothesis that random sampling subnet are the same probability distribution as the entire network if some conditions are met with, nodes’s degree in IP traffic can be processed as a power-law distribution in scale-free network . The model analyzes the power exponent and relations between the anomalous behavior and parameter r. Finally, a test was conducted by the data, some type attacks could be identified exactly. the model provides a new framework for intrusion-detection system.

You might also be interested in these eBooks

Frontiers of Manufacturing and Design Science

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 44-47)

Pages:

849-853

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.44-47.849

Citation:

Cite this paper

Online since:

December 2010

Authors:

Jun Li, Yan Niu

Keywords:

Power Exponent, Power Law, Scale-Free, Subset, Traffic Detection

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Albert-László Barabási, Emergence of scaling in random networks[J]．Science, 1999, 286(4)：509－512.

Google Scholar

[2] Albert-lászló Barabási , Zoltán Dezső , Erzsébet Ravasz , Zoltán Oltvai, Scale-free and hierarchical structures in complex networks, (November 25, 2002) Sitges Proc. on Complex Networks.

Google Scholar

[3] BARABASI, A. L., H. JEONG, Z. NEDA, E. RAVASZ, A. SCHUBERT, andT. VIESEK, Evolution of the social network of scientific collaborations, PHYS-ICA A 311 (Jan. 2002), 590–614.

Google Scholar

[4] Réka Albert, Scale-free networks in cell biology, Journal of Cell Science 118, 4947-4957 (2005).

DOI: 10.1242/jcs.02714

Google Scholar

[5] Maslov, S. & Sneppen, H. (2002) Science 296, 910–913.

Google Scholar

[6] Girvan, M. & Newman, M. J. E. (2002) Proc. Natl. Acad. Sci. USA 99, 7821–7826.

Google Scholar

[7] Albert, R. & Barabasi, A. L. (2002) Rev. Mod. Phys. 74, 47–97.

Google Scholar

[8] Michael P. H. Stumpf, Carsten Wiuf, and Robert M. May Sampling properties of networks, PNAS 2005 102: 4221-4224.

Google Scholar

[9] PEI Wei-dong, LIU Zhong-xin, CHEN Zeng-qiang, YUAN Zhu-zhi, Novel approach to design scale-free networks, J．University of hanghaifor Science andTechnology, Vo1. 30, No. 3, pp.158-176, March (2008).

Google Scholar

[10] R. Lippmann, et al., The 1999 DARPA Off-Line Intrusion Detection Evaluation, Computer Networks 34(4) 579-595, 2000. Data is available at http: /www. ll. mit. edu/IST/ideval.

DOI: 10.1016/s1389-1286(00)00139-0

Google Scholar