A machine-learning approach to phishing detection and defense / Oluwatobi Ayodeji Akanbi, Iraj Sadegh Amiri, Elahe Fazeldehkordi.

Enhanced descriptions from Syndetics:

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