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A machine learning approach to phish...

Akanbi, Oluwatobi Ayodeji,

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A machine learning approach to phishing detection and defense /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	A machine learning approach to phishing detection and defense // Oluwatobi Ayodeji Akanbi, Iraj Sadegh Amiri, Elahe Fazeldehkordi.
作者:	Akanbi, Oluwatobi Ayodeji,
其他作者:	Amiri, Iraj Sadegh,
面頁冊數:	1 online resource (1 volume) :illustrations
標題:	Phishing. -
電子資源:	https://www.sciencedirect.com/science/book/9780128029275
ISBN:	9780128029466

A machine learning approach to phishing detection and defense /
Akanbi, Oluwatobi Ayodeji,

A machine learning approach to phishing detection and defense /Oluwatobi Ayodeji Akanbi, Iraj Sadegh Amiri, Elahe Fazeldehkordi. - 1 online resource (1 volume) :illustrations

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 organiza.

ISBN: 9780128029466Subjects--Topical Terms:

1640348
Phishing.
Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: HV6773.15.P45

Dewey Class. No.: 364.1633

A machine learning approach to phishing detection and defense /
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504 $a Includes bibliographical references.
520 $a 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 organiza.
650 0 $a Phishing. $3 1640348
650 0 $a Computer networks $x Security measures. $3 579161
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700 1 $a Fazeldehkordi, Elahe, $e author. $3 3389689
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