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Bimonthly Since 1986 |
ISSN 1004-9037
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Publication Details |
Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
Distributed by:
China: All Local Post Offices
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Abstract
Cybercrimes are becoming more widespread every day. Cybercrime techniques include phishing, where hackers try to steal personal data from users of websites by making websites that seem like authentic websites. Internet users are tricked into providing information about their identity, such as access credentials, credit or debit card information, and other details, through phishing attacks, which are unauthorised access. The anti-phishing field has developed a variety of strategies over the past few years. Even though, the problems still continue. An overview of several phishing attempts and information protection strategies is presented in this paper. The various strategies used by different authors over recent years will be thoroughly covered in this survey. This study looks for and highlights the top early techniques, such as supervised machine learning and deep learning, that may be utilised to build a hybrid model that can identify websites as benign or phishing with more precision and accuracy.
Keyword
Phishing; Legitimate; Websites detection; Machine-learning; Deep-learning.
PDF Download (click here)
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