A Machine-Learning Approach to Phishing Detection and Defense
By Iraj Sadegh Amiri, O. A. Akanbi, E. Fazeldehkordi
Publisher: Elsevier / Syngress
Final Release Date: December 2014
Pages: 100

Phishing is one of the most widely-perpetrated forms of cyber attack, used to gather sensitive information such as credit card numbers, bank account numbers, and user logins and passwords, as well as other information entered via a web site. The authors of A Machine-Learning Approach to Phishing Detetion and Defense have conducted research to demonstrate how a machine learning algorithm can be used as an effective and efficient tool in detecting phishing websites and designating them as information security threats. This methodology can prove useful to a wide variety of businesses and organizations who are seeking solutions to this long-standing threat. A Machine-Learning Approach to Phishing Detetion and Defense also provides information security researchers with a starting point for leveraging the machine algorithm approach as a solution to other information security threats.

  • Discover novel research into the uses of machine-learning principles and algorithms to detect and prevent phishing attacks
  • Help your business or organization avoid costly damage from phishing sources
  • Gain insight into machine-learning strategies for facing a variety of information security threats
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