DocumentCode :
2034743
Title :
Online phishing detection toolbar for transactions
Author :
Barraclough, P.A. ; Sexton, G. ; Aslam, N.
Author_Institution :
Comput. Sci. & Digital Technol, Univ. of Northumbria, Newcastle upon Tyne, UK
fYear :
2015
fDate :
28-30 July 2015
Firstpage :
1321
Lastpage :
1328
Abstract :
Phishing attacks are growing rapidly causing financial losses annually particularly in online transactions. Previous solutions exist to address phishing attacks including toolbars and filters that displays user warnings against phishing websites. Despite the existing solutions, there is still a lack of accuracy in real-time solutions causing inadequacy in online transactions. This paper extends our previous work [12] by developing an online toolbar which runs continuously in the background of Internet Explorer web browser checking all websites users request against a set-data in real-time. The proposed approach is a feature-based online toolbar using six sets of inputs, incorporating a voice generating user warning interface with a text directives and color status to detect phishing websites and alert users from phishing attacks. The new toolbar system has been vigorously evaluated using a wide-ranging websites including 200 Phishing websites, 200 suspicious websites and 200 legitimate websites which has demonstrated best performance (96%) compared to previous reported results in the field. The paper has contributed a novel voice generating user warning interface algorithm that has not been considered in phishing website detection field.
Keywords :
Web sites; computer crime; financial management; online front-ends; transaction processing; user interfaces; Internet Explorer web browser; financial losses; online phishing detection toolbar; online toolbar; online transaction; phishing Web sites; phishing attack; phishing website detection; user warning interface algorithm; Accuracy; Algorithm design and analysis; Browsers; Feature extraction; Image color analysis; Internet; Real-time systems; Online intelligent; feature-based; intelligent toolbar detection; phishing website detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Science and Information Conference (SAI), 2015
Conference_Location :
London
Type :
conf
DOI :
10.1109/SAI.2015.7237314
Filename :
7237314
Link To Document :
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