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

List of contents

1. Introduction
2. Literature Review
3. Research Methodology
4. Feature Extraction
5. Implementation and Result
6. Conclusions

Product details

• Authors: O. A. Akanbi, O.A. Akanbi, O.A. (Graduate student in Computer Science at Texas Tech University) Akanbi, I S Amiri, I. S. Amiri, I. S./ Akanbi Amiri, I.S. Amiri, I.S. Dr. Amiri, Iraj Sadegh Amiri, E. Fazeldehkordi, E. (Information Security researcher) Fazeldehkordi, E. Fazeldohkordi
• Publisher: ELSEVIER SCIENCE BV
• Languages: English
• Product format: Paperback / Softback
• Released: 10.12.2014
• EAN: 9780128029275
• ISBN: 978-0-12-802927-5
• No. of pages: 100
• Series: Syngress Media
• Subject: Natural sciences, medicine, IT, technology > IT, data processing > General, dictionaries