A Web Page Classification Method Based on TCP/IP Header Features

DOI

10.2991/icwcsn-16.2017.14How to use a DOI?

Keywords

web page classification; packet header feature; instance-based learning

Abstract

Web page classification has wide applications. Due to various types of web pages and vast amounts of network traffic, it is difficult to classify web pages by deeply inspecting the content of each packet. This paper presents a learning-based classification method according to TCP/IP header features. First, we propose an approach to select features and improve the Relief algorithm, which can pick features with robustness. Then we raise a labeling strategy to assign each feature with a label when training the classifier. Last, we put forward a learning-based classification method which takes labels and multi-layer semantics into consideration. The experiment results show that the proposed strategy can improve the processing speed and the accuracy of classification.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Di Huang
AU  - Xin-Yi Zhang
AU  - Qi-Wei Tang
PY  - 2016/12
DA  - 2016/12
TI  - A Web Page Classification Method Based on TCP/IP Header Features
BT  - Proceedings of the 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)
PB  - Atlantis Press
SP  - 61
EP  - 64
SN  - 2352-538X
UR  - https://doi.org/10.2991/icwcsn-16.2017.14
DO  - 10.2991/icwcsn-16.2017.14
ID  - Huang2016/12
ER  -