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  • 标题:Malicious Web Page Detection through Classification Technique: A Survey
  • 本地全文:下载
  • 作者:Dr. Jitendra Agrawal ; Dr. Shikha Agrawal ; Anurag Awathe
  • 期刊名称:International Journal of Computer Science & Technology
  • 印刷版ISSN:2229-4333
  • 电子版ISSN:0976-8491
  • 出版年度:2017
  • 卷号:8
  • 期号:1
  • 页码:74-79
  • 语种:English
  • 出版社:Ayushmaan Technologies
  • 摘要:A “malicious web page” refers to a web page that contains malicious content that can exploit a client–side computer system. Malicious website may be used as a weapon by cybercriminal to exploit various security threats such as phishing, drive-bydownload and spamming. Malicious Web sites are hurdle on the way ofInternet security. And used as a weapon to mount various security threat like phishing, drive-by-download and spamming. To handle there is need to develop an automatic system to recognized malicious website. This paper gives a bird eye over malicious web site,their vulnerability and recent research to recognize it. In this work various machine learning and graph based technique to detect malicious website are presented. This paper also include various feature extraction technique such as information gain, N-gram, score gram and confidence weighted scheme to study nature of malicious website. The goal of this survey is to provide a comprehensive review of different classification techniques in data mining.
  • 关键词:Malicious Web;Blacklisting;Phishing;Machine Learning Technique;Http Response Graph
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