A Machine-Learning Approach to Phishing Detection and Defense
Amiri, I.S.
Akanbi, O.A.
Fazeldehkordi, E.
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 attacksHelp your business or organization avoid costly damage from phishing sourcesGain insight into machine-learning strategies for facing a variety of information security threats INDICE: IntroductionLiterature ReviewResearch MethodologyFeature ExtractionImplementation and ResultConclusions
- ISBN: 978-0-12-802927-5
- Editorial: Syngress
- Encuadernacion: Rústica
- Páginas: 100
- Fecha Publicación: 08/12/2014
- Nº Volúmenes: 1
- Idioma: Inglés