Illegal Network Identification Optimization Based on Convolutional Neural Network

DOI

10.2991/ncce-18.2018.180How to use a DOI?

Keywords

Illegal Website, Convolutional Neural Network, Image Classification, Algorithm Structure, Application Analysis

Abstract

Convolutional neural network (CNN) was a widely used algorithm for image classification in the field of computer vision. At present, in terms of identification of illegal web pages, the main application methods rely on manpower too much, which is a costly and time-consuming method. This paper will apply the CNN algorithm to the identification of illegal networks, build a CNN algorithm framework on the server side of browsers and web pages. It can also use CNN's outstanding performance in image classification to classify images of illegal websites and conducts real-time data on illegal websites. This paper will introduce the CNN algorithm characteristics from the algorithm structure and function

Copyright

© 2018, 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  - Weibin Chen
AU  - Jinhua Yang
PY  - 2018/05
DA  - 2018/05
TI  - Illegal Network Identification Optimization Based on Convolutional Neural Network
BT  - Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)
PB  - Atlantis Press
SP  - 1074
EP  - 1077
SN  - 1951-6851
UR  - https://doi.org/10.2991/ncce-18.2018.180
DO  - 10.2991/ncce-18.2018.180
ID  - Chen2018/05
ER  -