Chinese Journal of Network and Information Security ›› 2017, Vol. 3 ›› Issue (8): 44-60.doi: 10.11959/j.issn.2096-109x.2017.00186

• Papers • Previous Articles     Next Articles

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

Zheng-qi WANG1,2(),Xiao-bing FENG1,2,Chi ZHANG1,2   

  1. 1 University of Science and Technology of China,Hefei 230026,China
    2 Key Laboratory of Electromagnetic Space Information,Chinese Academy of Sciences,Hefei 230026,China
  • Revised:2017-07-22 Online:2017-08-01 Published:2017-12-26
  • Supported by:
    The National Natural Science Foundation of China(61202140);The National Natural Science Foundation of China(61328208)


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.

Key words: malicious Web page detection, network security, machine learning, feature extraction

CLC Number: 

No Suggested Reading articles found!