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A machine learning approach to phish...

Akanbi, Oluwatobi Ayodeji,

A machine learning approach to phishing detection and defense /

紀錄類型:	書目-電子資源 : Monograph/item
杜威分類號:	364.1633
書名/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.
標題:	Computer networks - Security measures.
ISBN:	9780128029466
ISBN:	0128029463
ISBN:	9780128029275
ISBN:	0128029277
書目註:	Includes bibliographical references.
摘要、提要註:	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.
電子資源:	https://www.sciencedirect.com/science/book/9780128029275

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:

708894
Phishing.
Index Terms--Genre/Form:

336502
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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020 $a 0128029463 $q (electronic bk.)
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100 1 $a Akanbi, Oluwatobi Ayodeji, $e author. $3 716032
245 1 2 $a A machine learning approach to phishing detection and defense / $c Oluwatobi Ayodeji Akanbi, Iraj Sadegh Amiri, Elahe Fazeldehkordi.
264 1 $a Waltham, MA : $b Syngress, $c 2015.
300 $a 1 online resource (1 volume) : $b illustrations
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338 $a online resource $b cr $2 rdacarrier
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 708894
650 0 $a Computer networks $x Security measures. $3 341462
655 4 $a Electronic books. $2 local $3 336502
700 1 $a Amiri, Iraj Sadegh, $d 1977- $e author. $3 715917
700 1 $a Fazeldehkordi, Elahe, $e author. $3 716033
856 4 0 $u https://www.sciencedirect.com/science/book/9780128029275

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