Machine learning approach to phishing detection and defense
By: Akanbi, Oluwatobi Ayodeji.
Contributor(s): Amiri, Iraj Sadegh [author] | Fazeldehkordi, Elahe [author].
Material type:
BookPublisher: Amsterdam : Syngress, 2015Description: xiv, 84p. : ill. ; 24 cm.ISBN: 9780128029275.Subject(s): Phishing | Social Science - Criminology | Computer networks - Security measuresDDC classification: 364.168 Summary: 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.
| Item type | Current location | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
| Books | 364.168 AKA (Browse shelf) | Available | 031751 |
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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.
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