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Author Akanbi, Oluwatobi Ayodeji, author.

Title A machine-learning approach to phishing detection and defense / Oluwatobi Ayodeji Akanbi, Iraj Sadegh Amiri, Elahe Fazeldehkordi.

Imprint Amsterdam : Elsevier, [2014]
Publication Info. ©2015

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Location Call No. OPAC Message Status
 Axe Elsevier ScienceDirect Ebook  Electronic Book    ---  Available
Description 1 online resource
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
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. 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.
Bibliography Includes bibliographical references.
Subject Phishing.
Computer networks -- Security measures.
Hameçonnage.
Réseaux d'ordinateurs -- Sécurité -- Mesures.
SOCIAL SCIENCE -- Criminology.
Computer networks -- Security measures
Phishing
Added Author Amiri, Iraj Sadegh, 1977- author.
Fazeldehkordi, Elahe, author.
Other Form: Erscheint auch als: Druck-Ausgabe Amiri, I.S.A Machine-Learning Approach to Phishing Detection and Defense
ISBN 1322480850 (electronic bk.)
9781322480855 (electronic bk.)
9780128029466 (electronic bk.)
0128029463 (electronic bk.)
9780128029275
Standard No. AU@ 000058374637
CHBIS 010547584
CHNEW 001012639
CHVBK 341781193
DEBBG BV043616388
DEBSZ 42790238X
DEBSZ 431876347
GBVCP 817109943
NZ1 15919170

 
    
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