Intelligent rule‐based phishing websites classification-Reference-Cited by-同舟云学术

Intelligent rule‐based phishing websites classification

Published:2014-05 Issue:3 Volume:8 Page:153-160
ISSN:1751-8717
Container-title:IET Information Security
language:en
Short-container-title:IET Information Security

Author:

Mohammad Rami M.¹,Thabtah Fadi²,McCluskey Lee¹

Affiliation:

1. School of Computing and EngineeringUniversity of HuddersfieldHuddersfieldUK

2. School of MISPhiladelphia UniversityAmmanJordan

Publisher

Institution of Engineering and Technology (IET)

Subject

Computer Networks and Communications,Information Systems,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ifs.2013.0202

Reference30 articles.

1. Sanglerdsinlapachai N. Rungsawang A.: ‘Using domain top‐page similarity feature in machine learning‐based web’.Third Int. Conf. Knowledge Discovery and Data Mining 2010 pp.187–190

2. Sophie G.P. Gustavo G.G. Maryline L.: ‘Decisive heuristics to differentiate legitimate from phishing sites’.Proc. 2011 Conf. Network and Information Systems Security 2011 pp.1–9

3. CANTINA +: a feature‐rich machine learning framework for detecting phishing web sites;Guang X.;ACM Trans. Inf. Syst. Secur.,2011

4. Rule induction‐machine learning techniques;Donald J.H.;Comput. Control Eng. J.,1994

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