A machine-learning approach to phishing detection and defense / [electronic resource] Oluwatobi Ayodeji Akanbi, Iraj Sadegh Amiri, Elahe Fazeldehkordi. Akanbi, Oluwatobi Ayodeji, author. Amiri, Iraj Sadegh, 1977- author. Fazeldehkordi, Elahe, author. Phishing. Computer networks Security measures. HV6773.15.P45 364.168 23 Includes bibliographical references. 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. Amsterdam : Elsevier, 2014 2014 2014 Text 1 online resource http://www.sciencedirect.com/science/book/9780128029275 eng Druck-Ausgabe Amiri, I.S.A Machine-Learning Approach to Phishing Detection and Defense Druck-Ausgabe Amiri, I.S.A Machine-Learning Approach to Phishing Detection and Defense