User Behavioral Characteristics Mining Algorithms Based on Net-Flow

Wei Hua Wang

doi:10.4028/www.scientific.net/AMR.791-793.1130

Paper Titles

A Simulated Annealing Based Algorithm for Energy-Constrained Ferry Route Design Problem
p.1113

Solving Closed Walk Ferry Route Design Problem by Using an Improved Genetic Algorithm
p.1117

An Improved Particle-Based Coupling Method of Fluid and Rigid Bodies
p.1121

Application of Principal Component Algorithm to the Direct Assimilation of AIRS in the WRF 4D-Var System
p.1125

User Behavioral Characteristics Mining Algorithms Based on Net-Flow
p.1130

A New GO Methodology Algorithm Based on BDD
p.1134

Simulation of Ocean Wave-Generated Magnetic Field Disturbance Observed above Sea-Surface Based on Directional Spectrum
p.1139

The High Performance Computing of Inversion Algorithms
p.1145

A Fast Algorithm for Anti-Collision in RFID System
p.1149

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 791-793User Behavioral Characteristics Mining Algorithms...

User Behavioral Characteristics Mining Algorithms Based on Net-Flow

Abstract:

Network security technology-based firewall, intrusion detection, less user behavior from the network point of view to is considered possible vandalism. Net Flow collector for this problem, the network traffic statistics, the design of said data structures and statistical models of user behavior characteristics, the behavior of specific information, the establishment of the database behavior in a certain period of time granularity; on the basis of the behavior of database the design the clustering mining algorithm applicable to user behavior features, defined from the user behavior, determine the behavior patterns of individual users of the network. The experiments show that the design algorithm can effectively tap the behavior of the user's network, and provide a valid basis for management, analysis of user behavior.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 791-793)

Pages:

1130-1133

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.791-793.1130

Citation:

Cite this paper

Online since:

September 2013

Authors:

Wei Hua Wang

Keywords:

Data Mining (DM), Net Flow, User Behavioral Characteristics

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Hong Tang, Shasha Xiao, Guofeng Zhao, Congcong Xing, Traffic Behaviors on the Mobile Internet, JCIT: Journal of Convergence Information Technology, Vol. 7, No. 7, pp.182-190, (2012).

Google Scholar

[2] Sang Wan KIM, Joon Kyung Lee, Jong Dae Park, Sang Ha KIM, User's behavior based Internet traffic Control in time period, JCIS: Journal of Communications and Information Sciences, Vol. 2, No. 2, pp.37-43, (2012).

Google Scholar

[3] Licai Wang, Xiangwu Meng, A MAUT Approach to Elicitation of Contextual User Preferences, AISS: Advances in Information Sciences and Service Sciences, Vol. 4, No. 5, pp.98-105, (2012).

DOI: 10.4156/aiss.vol4.issue5.12

Google Scholar

[4] Yingxu Lai, Xin Xu, Zhen Yang, Zenghui Liu, User Interest Prediction Based on Behaviors Analysis, JDCTA: International Journal of Digital Content Technology and its Applications, Vol. 6, No. 13, pp.192-204, (2012).

DOI: 10.4156/jdcta.vol6.issue13.22

Google Scholar

[5] Chuan Xu, Mei Wang, Hong Tang, Analysis on User Click Behavior in the Mobile Internet, JDCTA: International Journal of Digital Content Technology and its Applications, Vol. 5, No. 6, pp.16-23, (2011).

DOI: 10.4156/jdcta.vol5.issue6.3

Google Scholar