TY  - BOOK
AU  - Akanbi,Oluwatobi Ayodeji
AU  - Amiri,Iraj Sadegh
AU  - Fazeldehkordi,Elahe
TI  - A machine-learning approach to phishing detection and defense
SN  - 1322480850
AV  - HV6773.15.P45 
U1  - 364.168 23
PY  - 2015///
KW  - Phishing
KW  - Computer networks
KW  - Security measures
N1  - Includes bibliographical references
N2  - 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
UR  - https://www.sciencedirect.com/science/book/9780128029275
ER  -