A machine-learning approach to phishing detection and defense /

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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 Det...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Akanbi, Oluwatobi Ayodeji (Autor), Amiri, Iraj Sadegh, 1977- (Autor), Fazeldehkordi, Elahe (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Amsterdam : Elsevier, [2014]
�2015
Temas:
Phishing.
Computer networks > Security measures.
Hame�connage.
R�eseaux d'ordinateurs > S�ecurit�e > Mesures.
SOCIAL SCIENCE > Criminology.
Computer networks > Security measures
Phishing
Acceso en línea:Texto completo

MARC

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100 1 |a Akanbi, Oluwatobi Ayodeji,  |e author. 
245 1 2 |a A machine-learning approach to phishing detection and defense /  |c Oluwatobi Ayodeji Akanbi, Iraj Sadegh Amiri, Elahe Fazeldehkordi. 
260 |a Amsterdam :  |b Elsevier,  |c [2014] 
264 4 |c �2015 
300 |a 1 online resource 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
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 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. 
504 |a Includes bibliographical references. 
650 0 |a Phishing. 
650 0 |a Computer networks  |x Security measures. 
650 6 |a Hame�connage.  |0 (CaQQLa)201-0425882 
650 6 |a R�eseaux d'ordinateurs  |x S�ecurit�e  |x Mesures.  |0 (CaQQLa)201-0263812 
650 7 |a SOCIAL SCIENCE  |x Criminology.  |2 bisacsh 
650 7 |a Computer networks  |x Security measures  |2 fast  |0 (OCoLC)fst00872341 
650 7 |a Phishing  |2 fast  |0 (OCoLC)fst01737436 
700 1 |a Amiri, Iraj Sadegh,  |d 1977-  |e author. 
700 1 |a Fazeldehkordi, Elahe,  |e author. 
776 0 8 |i Erscheint auch als:  |n Druck-Ausgabe  |t Amiri, I.S.A Machine-Learning Approach to Phishing Detection and Defense 
856 4 0 |u https://sciencedirect.uam.elogim.com/science/book/9780128029275  |z Texto completo 

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