|Table of Contents|

Remote detection of web page tampering based on deep learning(PDF)

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2020年01期
Page:
49-54
Research Field:
Publishing date:

Info

Title:
Remote detection of web page tampering based on deep learning
Author(s):
Yin Jie1Jiang Yuxiang12Niu Bowei2Yan Zichen12Guo Yanwen34
1.Department of Network Security Corps,Jiangsu Police Institute,Nanjing 210031,China; 2.Jiangsu Public Security Bureau,Nanjing 210024,China; 3.Department of Computer Science and Technology,Nanjing University,Nanjing 210023,China; 4.State Key Laboratory for Novel Software Technology,Nanjing University,Nanjing 210023,China
Keywords:
web page tampering hidden hyperlink detection neural network deep learning network representation learning
PACS:
TP393.08
DOI:
10.14177/j.cnki.32-1397n.2020.44.01.008
Abstract:
The paper proposes a method that can detect attacks of web page tampering based on corpus construction and deep learning,which can obtain results with high precision and recalling. This paper obtains a large amount of web pages which are potentially tampered,and manually builds the web page tampering database based on the method of corpus construction. Secondly,this paper proposes an automatic detection algorithm based on deep neural network,which integrates text features,structure features and network features. The proposed method can predict whether a webpage has been tampered or not,as well as the attack type. Extensive experiments are conducted to show the effectiveness of the proposed method,with accuracy of 95.6%,recall of 96.7%,and F value of 96.1%,which significantly outperforms the baseline method.

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Last Update: 2020-02-29