Phishing Websites Detection using Machine Learning
作者: Arun KulkarniLeonard L. Brown III
刊名: International Journal of Advanced Computer Science and Applications (IJACSA), 2019, Vol.10
来源数据库: The Science and Information Organization(SAI)
DOI: 10.14569/IJACSA.2019.0100702
关键词: Phishing websitesClassificationFeaturesMachine learning
原始语种摘要: Tremendous resources are spent by organizations guarding against and recovering from cybersecurity attacks by online hackers who gain access to sensitive and valuable user data. Many cyber infiltrations are accomplished through phishing attacks where users are tricked into interacting with web pages that appear to be legitimate. In order to successfully fool a human user, these pages are designed to look like legitimate ones. Since humans are so susceptible to being tricked, automated methods of differentiating between phishing websites and their authentic counterparts are needed as an extra line of defense. The aim of this research is to develop these methods of defense utilizing various approaches to categorize websites. Specifically, we have developed a system that uses machine...
全文获取路径: SAI  (合作)

  • legitimate 合法
  • spent 消耗的
  • look 
  • learning 学识
  • interacting 相克的
  • recovering 恢复
  • successfully 成功地
  • distinguishing 判别
  • suspicious 可疑
  • classifier 分级机