A New Way for User's Web Communication Visualization and Measurement: Modeling, Experiment and Application

Tao QIN; Wei LI; Chenxu WANG; Xingjun ZHANG

doi:10.1587/transcom.E97.B.730

A New Way for User's Web Communication Visualization and Measurement: Modeling, Experiment and Application

Tao QIN, Wei LI, Chenxu WANG, Xingjun ZHANG

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With the ever-growing prevalence of web 2.0, users can access information and resources easily and ubiquitously. It becomes increasingly important to understand the characteristics of user's complex behavior for efficient network management and security monitoring. In this paper, we develop a novel method to visualize and measure user's web-communication-behavior character in large-scale networks. First, we employ the active and passive monitoring methods to collect more than 20,000 IP addresses providing web services, which are divided into 12 types according to the content they provide, e.g. News, music, movie and etc, and then the IP address library is established with elements as (service_type, IP_address). User's behaviors are complex as they stay in multiple service types during any specific time period, we propose the behavior spectrum to model this kind of behavior characteristics in an easily understandable way. Secondly, two kinds of user's behavior characters are analyzed: the character at particular time instants and the dynamic changing characters among continuous time points. We then employ Renyi cross entropy to classify the users into different groups with the expectation that users in the same groups have similar behavior profiles. Finally, we demonstrated the application of behavior spectrum in profiling network traffic patterns and finding illegal users. The efficiency and correctness of the proposed methods are verified by the experimental results using the actual traffic traces collected from the Northwest Regional Center of China Education and Research Network (CERNET).

Publication: IEICE TRANSACTIONS on Communications Vol.E97-B No.4 pp.730-737

Publication Date: 2014/04/01

Publicized

Online ISSN: 1745-1345

DOI: 10.1587/transcom.E97.B.730

Type of Manuscript: PAPER

Category: Network

Authors

Tao QIN
  Xi'an Jiaotong University
Wei LI
  Xi'an Jiaotong University
Chenxu WANG
  Xi'an Jiaotong University
Xingjun ZHANG
  Xi'an Jiaotong University

Keyword

web communication, behavior spectrum, visualization and measurement, clustering, traffic monitoring

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Tao QIN, Wei LI, Chenxu WANG, Xingjun ZHANG, "A New Way for User's Web Communication Visualization and Measurement: Modeling, Experiment and Application" in IEICE TRANSACTIONS on Communications, vol. E97-B, no. 4, pp. 730-737, April 2014, doi: 10.1587/transcom.E97.B.730.
Abstract: With the ever-growing prevalence of web 2.0, users can access information and resources easily and ubiquitously. It becomes increasingly important to understand the characteristics of user's complex behavior for efficient network management and security monitoring. In this paper, we develop a novel method to visualize and measure user's web-communication-behavior character in large-scale networks. First, we employ the active and passive monitoring methods to collect more than 20,000 IP addresses providing web services, which are divided into 12 types according to the content they provide, e.g. News, music, movie and etc, and then the IP address library is established with elements as (service_type, IP_address). User's behaviors are complex as they stay in multiple service types during any specific time period, we propose the behavior spectrum to model this kind of behavior characteristics in an easily understandable way. Secondly, two kinds of user's behavior characters are analyzed: the character at particular time instants and the dynamic changing characters among continuous time points. We then employ Renyi cross entropy to classify the users into different groups with the expectation that users in the same groups have similar behavior profiles. Finally, we demonstrated the application of behavior spectrum in profiling network traffic patterns and finding illegal users. The efficiency and correctness of the proposed methods are verified by the experimental results using the actual traffic traces collected from the Northwest Regional Center of China Education and Research Network (CERNET).
URL: https://globals.ieice.org/en_transactions/communications/10.1587/transcom.E97.B.730/_p

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@ARTICLE{e97-b_4_730,
author={Tao QIN, Wei LI, Chenxu WANG, Xingjun ZHANG, },
journal={IEICE TRANSACTIONS on Communications},
title={A New Way for User's Web Communication Visualization and Measurement: Modeling, Experiment and Application},
year={2014},
volume={E97-B},
number={4},
pages={730-737},
abstract={With the ever-growing prevalence of web 2.0, users can access information and resources easily and ubiquitously. It becomes increasingly important to understand the characteristics of user's complex behavior for efficient network management and security monitoring. In this paper, we develop a novel method to visualize and measure user's web-communication-behavior character in large-scale networks. First, we employ the active and passive monitoring methods to collect more than 20,000 IP addresses providing web services, which are divided into 12 types according to the content they provide, e.g. News, music, movie and etc, and then the IP address library is established with elements as (service_type, IP_address). User's behaviors are complex as they stay in multiple service types during any specific time period, we propose the behavior spectrum to model this kind of behavior characteristics in an easily understandable way. Secondly, two kinds of user's behavior characters are analyzed: the character at particular time instants and the dynamic changing characters among continuous time points. We then employ Renyi cross entropy to classify the users into different groups with the expectation that users in the same groups have similar behavior profiles. Finally, we demonstrated the application of behavior spectrum in profiling network traffic patterns and finding illegal users. The efficiency and correctness of the proposed methods are verified by the experimental results using the actual traffic traces collected from the Northwest Regional Center of China Education and Research Network (CERNET).},
keywords={},
doi={10.1587/transcom.E97.B.730},
ISSN={1745-1345},
month={April},}

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TY - JOUR
TI - A New Way for User's Web Communication Visualization and Measurement: Modeling, Experiment and Application
T2 - IEICE TRANSACTIONS on Communications
SP - 730
EP - 737
AU - Tao QIN
AU - Wei LI
AU - Chenxu WANG
AU - Xingjun ZHANG
PY - 2014
DO - 10.1587/transcom.E97.B.730
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E97-B
IS - 4
JA - IEICE TRANSACTIONS on Communications
Y1 - April 2014
AB - With the ever-growing prevalence of web 2.0, users can access information and resources easily and ubiquitously. It becomes increasingly important to understand the characteristics of user's complex behavior for efficient network management and security monitoring. In this paper, we develop a novel method to visualize and measure user's web-communication-behavior character in large-scale networks. First, we employ the active and passive monitoring methods to collect more than 20,000 IP addresses providing web services, which are divided into 12 types according to the content they provide, e.g. News, music, movie and etc, and then the IP address library is established with elements as (service_type, IP_address). User's behaviors are complex as they stay in multiple service types during any specific time period, we propose the behavior spectrum to model this kind of behavior characteristics in an easily understandable way. Secondly, two kinds of user's behavior characters are analyzed: the character at particular time instants and the dynamic changing characters among continuous time points. We then employ Renyi cross entropy to classify the users into different groups with the expectation that users in the same groups have similar behavior profiles. Finally, we demonstrated the application of behavior spectrum in profiling network traffic patterns and finding illegal users. The efficiency and correctness of the proposed methods are verified by the experimental results using the actual traffic traces collected from the Northwest Regional Center of China Education and Research Network (CERNET).
ER -