A Machine-Learning Approach to Phishing Detection and Defense

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9780128029275: A Machine-Learning Approach to Phishing Detection and Defense

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.

  • Discover novel research into the uses of machine-learning principles and algorithms to detect and prevent phishing attacks
  • Help your business or organization avoid costly damage from phishing sources
  • Gain insight into machine-learning strategies for facing a variety of information security threats

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About the Author:

Dr. Iraj Sadegh Amiri received his B. Sc (Applied Physics) from Public University of Urmia, Iran in 2001 and a gold medalist M. Sc. in optics from University Technology Malaysia (UTM), in 2009. He was awarded a PhD degree in photonics in Jan 2014. He has published well over 350 academic publications since the 2012s in optical soliton communications, laser physics, photonics, optics and nanotechnology engineering. Currently he is a senior lecturer in University of Malaysia (UM), Kuala Lumpur, Malaysia.

O.A. Akanbi received his B. Sc. (Hons, Information Technology - Software Engineering) from Kuala Lumpur Metropolitan University, Malaysia, M. Sc. in Information Security from University Teknologi Malaysia (UTM), and he is presently a graduate student in Computer Science at Texas Tech University His area of research is in CyberSecurity.

E. Fazeldehkordi received her Associate’s Degree in Computer Hardware from the University of Science and Technology, Tehran, Iran, B. Sc (Electrical Engineering-Electronics) from Azad University of Tafresh, Iran, and M. Sc. in Information Security from Universiti Teknologi Malaysia (UTM). She currently conducts research in information security and has recently published her research on Mobile Ad Hoc Network Security using CreateSpace.

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O. a. Akanbi, Iraj Sadegh Amiri, E. Fazeldehkordi
Editore: Syngress Media,U.S., United States (2014)
ISBN 10: 0128029277 ISBN 13: 9780128029275
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Descrizione libro Syngress Media,U.S., United States, 2014. Paperback. Condizione libro: New. Language: English . This book usually ship within 10-15 business days and we will endeavor to dispatch orders quicker than this where possible. Brand New Book. 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. Codice libro della libreria EOD9780128029275

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O. a. Akanbi, Iraj Sadegh Amiri, E. Fazeldehkordi
Editore: Syngress Media,U.S., United States (2014)
ISBN 10: 0128029277 ISBN 13: 9780128029275
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Descrizione libro Syngress Media,U.S., United States, 2014. Paperback. Condizione libro: New. Language: English . Brand New Book ***** Print on Demand *****.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. Codice libro della libreria AAV9780128029275

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AMIRI, I.S.; AKANBI, O.A.; FAZELDEHKORDI , E.
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ISBN 10: 0128029277 ISBN 13: 9780128029275
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Descrizione libro Syngress, 2014. Paperback. Condizione libro: NEW. 9780128029275 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. Codice libro della libreria HTANDREE0895985

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AMIRI, IRAJ SADEGH; AKANBI, O.A.; FAZELDEHKORDI , E.
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ISBN 10: 0128029277 ISBN 13: 9780128029275
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Descrizione libro Syngress, 2014. Paperback. Condizione libro: NEW. 9780128029275 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. Codice libro della libreria HTANDREE01200415

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Amiri, I S
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ISBN 10: 0128029277 ISBN 13: 9780128029275
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Descrizione libro Syngress, 2016. Paperback. Condizione libro: New. PRINT ON DEMAND Book; New; Publication Year 2016; Not Signed; Fast Shipping from the UK. No. book. Codice libro della libreria ria9780128029275_lsuk

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O. a. Akanbi, Iraj Sadegh Amiri, E. Fazeldehkordi
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ISBN 10: 0128029277 ISBN 13: 9780128029275
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Descrizione libro Syngress Media,U.S., United States, 2014. Paperback. Condizione libro: New. Language: English . Brand New Book ***** Print on Demand *****. 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. Codice libro della libreria AAV9780128029275

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Descrizione libro Syngress Media,U.S., 2014. PAP. Condizione libro: New. New Book.Shipped from US within 10 to 14 business days.THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice libro della libreria IP-9780128029275

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Amiri, I. S.
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Descrizione libro Syngress Media,U.S., 2014. PAP. Condizione libro: New. New Book. Delivered from our US warehouse in 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND.Established seller since 2000. Codice libro della libreria IP-9780128029275

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Iraj Sadegh Amiri; O.A. Akanbi; E. Fazeldehkordi
Editore: Syngress (2014)
ISBN 10: 0128029277 ISBN 13: 9780128029275
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Descrizione libro Syngress, 2014. Paperback. Condizione libro: New. book. Codice libro della libreria 0128029277

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Amiri, Iraj Sadegh
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Descrizione libro Syngress, 2017. Paperback. Condizione libro: New. This item is printed on demand. Codice libro della libreria 0128029277

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