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A Machine-Learning Approach to Phishing Detection and Defense

SKU: 978-0-12-802946-6 Categories: , ,

Product Description

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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detail product

  • Title : A Machine-Learning Approach to Phishing Detection and Defense
  • Author : I. S. Amiri, O. A. Akanbi, E. Fazeldehkordi
  • Publisher : Elsevier / Syngress
  • Pages : 100
  • Print ISBN :
  • Print ISBN 10 :
  • Ebook ISBN : 978-0-12-802946-6
  • ISBN 10 : 0-12-802946-3

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