Study of high-speed malicious Web page detection system based on two-step classifier

In view of the increasing number of new Web pages and the increasing pressure of traditional detection methods,the naive Bayesian algorithm and the support vector machine algorithm were used to design and implement a malicious Web detection system with both efficiency and function,TSMWD ,two-step ma...

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Bibliographic Details
Main Author: Zheng-qi WANG,Xiao-bing FENG,Chi ZHANG
Format: Article
Language:English
Published: POSTS&TELECOM PRESS Co., LTD 2017-08-01
Series:网络与信息安全学报
Subjects:
Online Access:http://www.infocomm-journal.com/cjnis/CN/10.11959/j.issn.2096-109x.2017.00186
Description
Summary:In view of the increasing number of new Web pages and the increasing pressure of traditional detection methods,the naive Bayesian algorithm and the support vector machine algorithm were used to design and implement a malicious Web detection system with both efficiency and function,TSMWD ,two-step malicious Web page detection.The first step of detection system was mainly used to filter a large number of normal Web pages,which was characterized by high efficiency,speed,update iteration easy,real rate priority.After the former filter,due to the limited number of samples,the main pursuit of the second step was the detection rate.The experimental results show that the proposed scheme can improve the detection speed of the system under the condition that the overall detection accuracy is basically the same,and can accept more detection requests in certain time.
ISSN:2096-109X