A Machine Learning Approach to Phishing Detection and Defense
- 1h 10m
- Elahe Fazeldehkordi, Iraj Sadegh Amiri, Oluwatobi Ayodeji Akanbi
- Elsevier Science and Technology Books, Inc.
- 2015
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 Detection 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 Detection 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
In this Book
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Abstract
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List of Abbreviation
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Introduction
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Literature Review
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Research Methodology
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Feature Extraction
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Implementation and Result
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Conclusions
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References
